When The Future Arrives

About fifteen years ago, I became fascinated by the Future of Work.

I spoke about it. Wrote about it. Read the futurists and trend spotters, followed the emerging technologies and tried to work out what they might do not only to jobs, but to organisations, leadership, learning and the experience of being at work. Like many people interested in this field, I became a collector of signals. Small indications that something previously improbable was becoming possible.

And the future was rather obliging in those days, because it came with things.

3D printing. Electric and autonomous vehicles. Quadcopters and UAVs (before we all simply called them drones). Artificial intelligence and machine learning. Quantum computing. Blockchain. Bitcoin and cryptocurrencies. Later, DAOs and NFTs. Robotics. Virtual and augmented reality. The gig economy. Universal Basic Income. Nanotechnology. Synthetic biology. Protein folding. The tantalising prospect of abundant clean energy. Production costs falling towards zero.

You could point at the future.

You could put it on a slide.

And I did.

I recently went back through a deck I used around 2016/2017 called The 7 Dimensions of the Future of Work. There they all are. Robotics, UAVs, autonomous vehicles, AI, data analytics, machine learning, automation, bots, quantum computing, augmented humans, nanotechnology, new interfaces, 3D printing, the gig economy, blockchain and cryptocurrencies.

There’s even the Local Motors Strati, the 3D-printed car that seemed for a while to represent a completely different future of manufacturing.

Looking through those slides now is an odd experience.

Some of it happened. Some of it happened differently. Some things became far bigger than I imagined. Some never got anywhere near the scale their advocates promised. Some were useful technologies burdened with absurd expectations. Some became everyday infrastructure and consequently disappeared from our sense of what was futuristic at all.

I was, I think, about as right as I could reasonably have been. But that’s not really the point.

Because just this week, I’ve been wondering why I couldn’t simply sit down now and do it again.

The Future of Work: Part Two.

Another deck. Another set of technologies. Another seven dimensions perhaps. Another horizon filled with interesting things that are currently peripheral but will become mainstream sometime around 2035 or 2040.

Except I don’t think I can. And, more importantly, I don’t think anybody really can in quite the same way.

Something has changed in our relationship with the future.

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When the future had things in it

The Future of Work industry - and it did become something of an industry - was extraordinarily good at nouns.

Robots. Drones. Blockchain. Crypto. 3D printers. Autonomous cars. Virtual reality. Artificial intelligence.

The nouns gave the future shape.

They gave us something to investigate and something to build scenarios around.

• What happens when cars drive themselves?

• What happens when robots take over repetitive work?

• What happens when almost anything can be 3D printed?

• What happens when transactions no longer require traditional intermediaries?

• What happens when machines can learn?

Some of the answers turned out to be more prosaic than the questions.

3D printing didn’t put a factory in every home, but it became an important manufacturing technology.

Crypto didn’t replace money. Blockchain didn’t replace the institutions of trust. DAOs haven’t made conventional organisational structures obsolete. NFTs briefly appeared to have discovered a completely new economics of ownership before becoming one of the more spectacular examples of hype colliding with reality.

The Metaverse was going to become the place we worked, met, played and perhaps even lived. Organisations bought virtual land. Consultancies created Metaverse practices. We were told to prepare ourselves for offices populated by avatars without legs.

Then most of us carried on using Microsoft Teams.

None of this means those technologies were necessarily failures.

That’s too simplistic. Technologies find applications, mutate, combine with other technologies and sometimes become useful in ways considerably less dramatic than the futures originally constructed around them.

But something else happened.

Many of the technologies we were waiting for simply arrived. And once they arrived, we stopped noticing them.

The smartphone ceased to be futuristic. Cloud computing ceased to be futuristic. Video collaboration ceased to be futuristic. Algorithms choosing what we see ceased to be futuristic. Talking to machines ceased to be particularly futuristic.

The future has a peculiar habit of becoming ordinary.

Perhaps that is the first part of the problem.

Seven dimensions, nine years later

The technology slides in my old deck are interesting, but looking at them now, they’re not what intrigues me most.

Because underneath all those shiny objects I had coded something else: seven shifts I thought would characterise the emerging world of work.

I called them the 7Ds:

• Digitisation and Socialisation of Work;

• Decline of the Job;

• Demise of the Manager;

• Death of the Hierarchy;

• Democratisation of Learning;

• Disruption as Usual; and

• Demand for Craft.

I wouldn’t claim that jobs, managers or hierarchies are dead. Clearly they’re not. That wasn’t really the interesting part of those predictions anyway.

It was the direction of travel.

• Under Decline of the Job, for example, I wrote: work not jobs; work as a platform; workforce on demand.

• Under Demise of the Manager: coach, mentor, Scrum Master, lead from within.

• Under Death of the Hierarchy, I talked about the dawn of the wirearchy - agile, adaptable and flat.

• Learning would become social, emergent, miniaturised and playlisted.

• Disruption would become normalised.

• And despite all this technology, I thought we would see an increasing demand for craft: making, artistic expression and purpose-led work.

Those feel rather more interesting in 2026 than whether I successfully spotted drones.

Those weren’t really predictions about technology. They were predictions about how work might reorganise itself around technology. And I think that distinction matters enormously now.

Jobs haven’t vanished, but we increasingly talk about skills, tasks, projects, gigs, missions, outcomes, fractional roles, and portfolios of contribution.

Managers haven’t disappeared, but the expectation that their principal function is to allocate and supervise work feels increasingly archaic.

Hierarchies remain extraordinarily resilient, but alongside them we now have networks, platforms, communities, ecosystems, agile teams and increasingly autonomous units.

Learning has escaped the classroom almost completely. We search, watch, listen, converse, generate, experiment and learn at the point of need. And now we can summon something resembling a personal tutor, researcher or coach simply by opening an AI interface.

Perhaps most intriguing of all is that demand for craft.

It appears we are entering an era in which synthetic production could become almost infinite. Words, images, video, music, code, analysis and ideas can increasingly be generated in seconds.

When production becomes abundant, the scarce thing may turn out to be judgement. Taste. Care. Discernment. Provenance. The knowledge that somebody actually meant something when they made it.

The more abundant machine capability becomes, perhaps the more we value distinctively human craft.

I didn’t predict all of that. But I think I caught the direction.

And that’s precisely why I find myself unable to produce The Future of Work: Part Two.

Where have all the things gone?

What would I put in the equivalent slide now?

AI, obviously. Except AI was already on the 2017 slide.

Robotics? Already there.

Quantum computing? There.

Autonomous vehicles? There.

Augmented humans? There.

New interfaces? There.

The biological sciences and genetic engineering would deserve far more prominence now. Clean energy and storage perhaps. Spatial computing. Humanoid robotics. Brain-computer interfaces. Agentic systems.

But something feels different.

It isn’t that technological innovation has slowed down. Almost absurdly, the opposite is true. It is more that such technologies are becoming harder to treat as separate futures.

• AI meets robotics; meets biology; meets materials science; meets medicine.

• AI meets energy systems.

• AI meets organisational design.

• AI meets education.

• AI meets individual human agency.

• AI meets another AI.

The interesting developments increasingly happen between the categories.

Perhaps we have moved from an age of invention into an age of extraordinary recombination. Not because invention has stopped, but because so many powerful capabilities are now available simultaneously that their intersections may matter more than any individual technology.

And that makes the future much harder to put on a slide.

There may no longer be a neat collection of things waiting patiently over the horizon for us to discover them.

The future is becoming ambient.

The boxset that never ends

I’ve been trying to find an analogy for this and I think it’s the difference between waiting for the next film in a series and discovering that you’re actually inside a boxset that never ends.

There isn’t going to be Future of Work II: The Sequel. We’re already watching it.

The next episode starts automatically before we’ve properly processed the previous one. Characters appear and disappear. Something that looked central to the plot three episodes ago is barely mentioned again. A minor character suddenly becomes the entire storyline. Several plots begin to converge. Occasionally you realise that something happening now was foreshadowed years earlier.

And, after a while, you stop noticing that you’re watching the future at all.

You just keep watching.

That’s what I think has happened: The Future of Work hasn’t ended. It has lost its episodic quality.

There is no obvious point at which we can say: that was the old world; here comes the new one.

AI doesn’t arrive on Tuesday and transform the organisation by Friday. It leaks into workflows. Someone experiments with it. Someone else quietly automates something. A team changes how it produces work. A role begins to alter. A capability that once required specialist expertise becomes widely accessible. A process disappears. A new one forms. Expectations change. Then behaviours. Then perhaps structures.

By the time somebody announces that the future has arrived, people have been living in it for years.

Which means the future may no longer be primarily about things. It may be about conditions.

From nouns to verbs

As I said at the top of this piece, the “old” future was remarkably noun-shaped.

Blockchain. Robots. Drones. Crypto. 3D printing. AI.

I wonder whether the emerging future is better understood through verbs.

Adapting. Learning. Generating. Sensing. Reconfiguring. Combining. Orchestrating. Augmenting. Collaborating. Becoming.

And for me, that changes the question of what this “new” future is all about.

Instead of asking, what technology comes next? perhaps we ask

• What happens when intelligence becomes abundant?

• What happens when knowledge that once took hours to find can be synthesised in seconds?

• What happens when expertise becomes more accessible?

• What happens when machines don’t merely execute instructions but increasingly participate in interpreting, generating and coordinating work?

• What happens when the boundaries between employee, freelancer, machine, agent, platform and organisation become increasingly porous?

And

• What happens to an organisation when its environment can change faster than its organisational chart?

These aren’t really technology questions - they’re questions about agency, identity, power, knowledge, coordination and organisational form.

Which brings me, inevitably, to Polymorphic Organisations. Because I increasingly think the most important Future of Work question isn’t what is coming…

It’s what kind of organisation can live with whatever comes?

That is a very different proposition.

For decades, strategy and organisational design have been built partly on the assumption that we can establish enough certainty about the environment to design an organisation appropriate to it. We forecast, decide, structure, implement and then periodically reorganise when reality has moved sufficiently far away from our assumptions.

It’s likely - if not definitively - that rhythm is becoming untenable.

If the next decade (the “new” future of work) really is combinatorial; (what a word - I’ve longed to use that in a blog post for ages) and if technological capabilities continue to interact and accelerate; and if work itself becomes more fluid; along with human and machine agency increasingly coexisting; then the organisation designed for a particular predicted future may be obsolete before it gets there.

This is also the entire premise of my good friend Erik Korsvik Ostergaard’s work on Futures literacy and Futures Thinking. STOP predicting the future and use the possibilities, plausibilities and preferences to USE the future (or futures - plural).

The advantage therefore isn’t prediction.

It is optionality.

The capacity to sense and respond. To expand and consolidate. To distribute intelligence without losing coherence. To move people and capabilities towards emerging needs. To form structures without becoming imprisoned by them. To know when stability is useful and when it has become inertia.

This is why I’ve become increasingly interested in organisations as things capable of changing form rather than periodically undergoing transformation.

Polymorphism isn’t about perpetual disruption. Organisms don’t continuously mutate for the excitement of it. Healthy systems contain periods of stability, repetition, consolidation and rest. But they retain the capacity to alter their configuration when circumstances require it.

Maybe that is what replaces the old Future of Work conversation.

Not prediction, but preparedness.

Not futurism as a collection of shiny objects, but futures capability embedded in the organisation itself.

Perhaps the future has lost its iconography

There’s another thought I can’t quite shake.

Every previous conception of the future seems to have had an iconography.

The mid-twentieth-century future gave us rockets, monorails, silver suits and cities in the sky. Later came personal computers, mobiles, GPS and cyberspace. The 2010s gave us drones, VR headsets, driverless cars, Bitcoin symbols, 3D printers and robots.

What is the image of 2035?

• A humanoid robot?

• Smart glasses?

• A quantum computer?

• A chatbot?

None seems remotely adequate. Perhaps that’s because what is changing now cannot easily be photographed.

• How do you photograph distributed intelligence?

• How do you draw abundant cognition?

• What does the dissolution of a job look like?

What’s the icon for a company whose boundaries continuously alter, whose people move between spaces of work, whose capabilities assemble around problems, whose artificial agents work alongside human ones and whose structure changes according to what the environment requires?

Maybe the absence of an obvious image of the future isn’t a failure of imagination. Maybe it’s a clue. The transformation isn’t principally in the artefacts anymore.

It’s in the relationships between them.

Between people and machines. Between knowledge and action. Between individuals and institutions. Between skills and work. Between authority and agency. Between stability and adaptation. Between organisation and environment.

That future is much harder to draw. But it may be much more consequential.

Be the futurologist?

There’s one final slide from that old deck that makes me smile.

It says “Be the Futurologist”, surrounded by four roles: Analyst, Anthropologist, Explorer and Hacker.

I still rather like that But I think I’d change the instruction now.

Not predict the future. Participate in it.

Sense it. Question it. Experiment with it. Learn from it. Notice what is becoming possible and what is quietly becoming obsolete. Pay attention not merely to new technologies but to the behaviours and relationships they make possible. Build organisations capable of responding before certainty arrives.

Because perhaps the Future of Work isn’t somewhere ahead of us anymore. Perhaps we’re inside it?

The technologies we once pointed towards have arrived around us in various states of triumph, disappointment, usefulness and absurdity. The next wave is already combining with this one before we’ve decided what this one meant.

There won’t be a clean ending, and there probably won’t be a sequel.

There’ll just be another episode, and another after that, each beginning before the credits have rolled on the last. And perhaps that is why the future feels strangely difficult to see.

We’re no longer looking at it. We’re watching it.

And most of the time, we won’t even notice that the next episode has begun.

So what do we do when the future won’t sit still?

And it won’t be photographed, iconised and certainly not woven in slide decks…

If all of this is true, it would be tempting to conclude that forecasting has become pointless. I don’t think that. Futures thinking, horizon scanning, scenarios and speculative work may matter more precisely because certainty has diminished.

What I think has changed is the purpose of thinking about the future, studying the future and even narrating the future.

We aren’t trying to get the future right. We’re trying to become less wrong-footed by it.

Not that I like half-measures or negatively framed anything. but I think this distinction matters. It certainly did to me in thinking why I can’t find the frames or words to describe “The Future of Work Part II”.

The conventional response to uncertainty is often to demand more prediction. Look back and go back even. Or seek more data to create “better forecasts”. A five-year strategy refreshed every three years. We try to reduce uncertainty until there is enough apparent solidity upon which to make a decision.

Perhaps the more useful response is almost the opposite.

Instead of asking how we can become better at predicting what the organisation will need to be in five years’ time, we could ask: How do we create an organisation capable of becoming several different things over those five years?

That is (partly) where the idea of the Polymorphic Organisation starts to move from interesting organisational theory into practical necessity.

Polymorphism, borrowed from biology and computer science, is - as I’ve written in almost every chronicle - the capacity for something to take different forms while retaining enough underlying coherence to remain itself.

Applied organisationally, it gives us a different ambition from the traditional transformation programme. We don’t transform from Organisation A into Organisation B, declare victory and then spend several years discovering that the environment has moved on again.

We build the capability to keep becoming.

That doesn’t mean permanent reorganisation. Frankly, that sounds exhausting and we’re all feeling that now.

It means developing enough responsiveness within the system that adaptation doesn’t always require another grand transformation programme.

And several of the ideas I’ve been exploring through these Chronicles begin to look less like separate organisational innovations and more like components of that capability.

• Organisational Oscillation, for example, accepts that organisations need different modes at different moments. There are times for exploration and expansion, experimentation and possibility; and there are times for consolidation, exploitation, standardisation and reliability. The answer isn’t to choose between agility and stability. It’s to become better at moving between them.

• Proficiency Stacks question the wisdom of trapping human capability inside static job descriptions. If the work changes continuously but our architecture of work assumes people occupy relatively fixed boxes, we have built rigidity into the very unit through which we organise contribution. Skills, capabilities and proficiencies give us something more recombinable.

• Spaces rather than Divisions asks a similar question of structure. What if people could gather around challenges, missions, customers, products or opportunities without every shift in strategic emphasis requiring us to redraw the hierarchy? Structure still matters, but perhaps it becomes more like scaffolding than concrete.

• Flywheels give us another alternative to the programme-and-project mentality. Instead of continually launching initiatives, exhausting everybody, closing them and launching replacements, we can create reinforcing loops of activity that build capability through use. Learning creates experimentation; experimentation creates evidence; evidence creates confidence; confidence creates greater agency; greater agency produces more learning. The organisation starts generating some of its own adaptive energy.

And then there is AI and agentic work, which may prove to be the accelerant underneath all of this.

Not simply AI as another productivity tool inserted into yesterday’s operating model, but intelligence becoming another organisational resource: available in different quantities, at different points, sometimes human, sometimes artificial and increasingly combined.

The question becomes less “where can we use AI?” and more “how does an organisation configure itself when cognition itself is increasingly distributed?”

These aren’t answers to the question what will the Future of Work look like? They’re responses to a different question:

What capabilities might an organisation need when we don’t know what the Future of Work will look like?

And I think there are some practical things we can start doing now. At the risk of repeating earlier chronicles, they’re bundled here:

1. We can get much better at sensing. Not another annual trends report destined for the corporate SharePoint, but deliberate mechanisms through which weak signals from technology, society, customers, employees, science, regulation and culture find their way into organisational conversations. Curiosity needs infrastructure.

2. We can increase optionality. Instead of making every strategic decision a large irreversible bet, we can run more experiments, prototypes, pilots and small probes. Futures become things we test rather than merely describe. Some options will close. Others will suddenly become valuable. The important thing is having some.

3. We can design for recombination. If capabilities, teams, technologies and resources can be assembled differently as circumstances change, then adaptability stops depending upon heroic leadership interventions. It becomes something the system can do.

4. We can become more deliberate about what should remain stable. Adaptability isn’t the worship of change. Some things should be stubborn: purpose, principles, relationships, trust, ethical boundaries, perhaps elements of identity and craft. A Polymorphic Organisation needs a strong enough core to support fluid edges. Otherwise polymorphism simply becomes chaos.
   

   - And perhaps most importantly -
   

5. We can shift our attention from change management to change capability.

We’ve spent decades becoming increasingly sophisticated at helping people through transformations conceived elsewhere. Maybe the more interesting challenge now is to create organisations in which people have enough information, agency, skill, psychological capacity and authority to participate in continuous adaptation themselves.

That is a very different social contract. And it takes me all the way back to those 7Ds.

• The Decline of the Job wasn’t really about abolishing jobs. It was about loosening the relationship between a person and a box.

• The Demise of the Manager wasn’t about getting rid of managers. It was about redistributing leadership.

• The Death of the Hierarchy wasn’t about pretending organisations need no structure. It was about creating other pathways through which information, influence and work could flow.

• The Democratisation of Learning wasn’t about putting courses online. It was about moving access to knowledge closer to the person who needs it.

• Disruption as Usual wasn’t a celebration of instability. It was recognition that adaptation would become ordinary.

• And Demand for Craft was perhaps the reminder underneath everything else that technology doesn’t automatically make work more human. We have to choose to make it so.

Seen that way, perhaps the 7Ds weren’t really predictions at all. They were early design principles. And that feels more important to me now.

From predicting futures to creating futurefulness

Perhaps there is a word for the capability I’m describing here: futurefulness.

Not future-proofing. I’ve never particularly liked that phrase because nothing is future-proof. It implies we can somehow build an organisational hull thick enough to prevent the future from getting in.

We need the opposite. We need organisations that let the future in.

Organisations curious enough to notice it, porous enough to learn from it, confident enough to experiment with it and fluid enough to alter themselves because of it — without losing the things that make them worth belonging to in the first place.

That is increasingly what these Polymorphic Chronicles are about. Not a model of the organisation of 2035. Not my attempt to draw the next organisational chart. Not another declaration that hierarchy is dead, AI will replace everybody, offices will disappear or jobs will cease to exist.

The Chronicles explore the properties organisations may need when permanence itself becomes less dependable.

How do we organise around capability rather than position? How does authority move closer to information? How do teams form and reform? How do organisations oscillate between exploration and consolidation? How can human and artificial intelligence work together? How do we create enough structure for coherence without producing so much structure that adaptation becomes an act of rebellion? How do we preserve craft, dignity, belonging and meaning while simultaneously becoming dramatically more fluid?

These are not questions about some distant future. They’re questions about next Tuesday.

And perhaps that is the biggest difference between my Future of Work work fifteen years ago and the work I’m doing now.

Back then, I was looking towards the horizon and asking:

What’s coming?

Now I’m much more interested in asking:

What are we becoming?

Because the future isn’t waiting somewhere in 2035 for us to arrive.

It’s continuously assembling itself from decisions being made today. From technologies being combined. From experiments being run. From assumptions being discarded. From new forms of work emerging inside old organisational structures. From people finding different ways to contribute, lead, learn and create.

There is no Future of Work: Part Two. There can’t be.

The sequel became a series, the series became a boxset, and now the boxset doesn’t even have seasons. It simply keeps streaming while we’re living our lives, occasionally asking whether we’re still watching.

We are. I hope.

The more useful question for organisations is whether we’re merely watching what happens next — or developing the capacity to change shape because of it.

Perhaps that is what being Polymorphic ultimately means.

Not knowing the future.

Being capable of meeting it.

I’ve added this now because, of course, I’m sparring with a GPT to get my thinking out, pan the research and science worlds and just shape my thoughts. Substack now scans posts to say “likely built by AI” or something similar.

We’re also - at the time of writing - seeing Anthropic’s Claude “watermarking” its text even when copied and pasted.

I don’t mind this. I’ve always used AI to spar with and produce, and I’ve always - and will forever - love the art/act of writing. Why would I want that outsourced/synthesised fully when I can have it augment and check what I’ve written?

Anyway, that out of the way, something’s occurred to me over the last few months. In looking at, particularly, leadership in organisations.

We are still being heroes, and we are still rewarding and deifying our heroes in leadership; instead of treating these things as signals of a system that shouldn’t need them as much as it does.

I’m not saying don’t be a hero.

Bystanders, pretenders, demagogues, psychopaths, and mediocrity are still in the leadership domain, and we may probably need heroes for those instances forever.

But as a norm, hero leadership worries me. Or even the thought that as a leader you are the ultimate hero in the story.

I recall the Ralph Nader quote:

“The function of leadership is to produce more leaders, not more followers.”

And yet some perceived wisdom will say we might have too many leaders now anyway. Why would we want more?

We haven’t got enough of the right sort of leaders: systems-savvy leaders. Not just architects of hierarchical spans of control or workflow kind of systems (important though they are).

I’m talking more about the systems of:

• Relational connection and human relationship building

• Prioritisation, alignment and congruence

• Inventive, creative and adaptive solutions and processes

• Incubation, development and future-focused thinking

• Capability and capacity building, of skills renewal and regeneration

• Energy, stamina, focus and health.

• Course-correcting, chaos management, complexity wrangling and so on and so forth.

And in some cases, I’ve observed not just an ambivalence to systems leadership, but a deliberate and wilful blindness or swerving of systems leadership in favour of more heroic leadership.

It seems we all want to do heroic leadership things as the calling card of being a good, strong, dependable and needed leader.

Because, taking those behaviours aside, what we’re doing is grafting heroic leaders into broken, failing, or inadequate systems.

We celebrate the person who gets things over the line, the leader who somehow cuts through the bureaucracy, the project manager who knows precisely which conversations need to happen outside the formal process, and the trusted operator who can summon resources, permissions and cooperation that seemingly remain unavailable to everyone else.

We call these people exceptional, reward their ingenuity and occasionally build succession plans around their indispensability.

Yet we rarely ask the more uncomfortable question: why did the organisation require heroics in the first place?

I have become increasingly convinced that this question points to something much bigger than leadership style or organisational culture.

It concerns the architecture of work itself, and particularly the extent to which many of the operating assumptions we inherited from the twentieth century remain embedded in organisations whose circumstances have changed almost beyond recognition.

We still organise extensively through functions, hierarchies, reporting lines, budgetary territories and relatively fixed distributions of authority. We still tend to regard the organisation chart as an adequate representation of the organisation, even though almost anyone who has spent time inside a complex institution knows it is nothing of the sort. Work travels through relationships, reputations, favours, communities, conversations, digital channels and informal networks. Expertise appears in unexpected places. Decisions frequently require combinations of knowledge that no single function possesses. Problems spill across the boundaries we have carefully constructed around them.

And so people adapt.

This capacity for adaptation is one of the extraordinary qualities of human systems, but it can also disguise poor design for a remarkably long time.

People compensate for unnecessary approvals, duplicate processes, incompatible systems and poorly distributed authority. They create spreadsheets because the enterprise platform doesn’t quite work. They establish unofficial WhatsApp groups because information travels too slowly through formal channels. They learn who really makes the decision rather than who is supposedly authorised to make it. They cultivate relationships with the people who can unblock things. They work longer, negotiate harder and carry increasingly elaborate maps of organisational idiosyncrasy in their heads.

The work continues, which allows the organisation to conclude that the system works.

But perhaps it doesn’t.

Perhaps the people are making it work despite the system.

From Absorption Debt to Heroic Debt

In Chronicle XIX, I explored an idea I called Absorption Debt: the accumulated organisational burden created when we continually absorb new technologies, processes, expectations, initiatives and adaptations without sufficiently redesigning or removing what came before them.

Organisations become sedimentary. Another layer is added, then another, until considerable human effort is required simply to navigate what has accumulated.

There may be a related phenomenon worth naming: Heroic Debt.

Heroic Debt accumulates whenever extraordinary human effort becomes the recurring mechanism through which an organisation compensates for deficiencies in its design.

Like other forms of debt, it can be deceptively useful in the short term. A brilliant individual circumvents a process, a respected leader brokers peace between competing functions, or a committed team works through the weekend and the immediate problem disappears. The organisation benefits while quietly carrying forward the underlying liability.

Over time, heroics become institutionalised.

We know the language because it sounds so benign:

• Mo always gets things over the line in board meetings.

• Ash knows how to work a to a decision when it gets tense.

• Lee can get Finance to agree, whatever the budget constraints.

• Jo knows who actually makes the decision in the Non-Execs.

These are undoubtedly statements about human capability, but they may simultaneously be statements about organisational failure. The indispensable individual is sometimes simply the person who has accumulated enough tacit knowledge, relational capital and political dexterity to compensate for an architecture that makes ordinary work unnecessarily difficult.

Their indispensability is a diagnostic. Linked to the Absorption debt (poor processes, overbearing bureaucracy) in their teams, Hero debt is slightly different. It’s more intoxicating than tiring. It’s more ego-flattering than deflating, and it’s more of a rite of passage than the wrong things happening.

Which is probably why we’re stuck with Hero debt until we do something more systemic to remove this as an option, even if people continually want to choose and be it.

Systems Thinking probably always wins.

This is where systems thinking becomes particularly important.

Ackoff, Deming and others repeatedly warned against the assumption that improving or managing individual components necessarily improves the performance of the whole.

A system possesses properties that emerge from the relationships between its parts, and yet much conventional Organisation Design continues to privilege the parts.

We establish functions, appoint leaders to optimise them, give those leaders budgets and targets, assess their performance against functional outcomes and then express frustration when the resulting organisation behaves territorially.

We construct the territories and subsequently launch programmes asking people to collaborate across them.

It’s in the psychology of it all, of course. The research on psychology is helpful in understanding this before we just label Systems Thinking as the silver bullet.

Psychological ownership and organisational territoriality suggests that people can develop powerful attachments to things they perceive as theirs: knowledge, roles, teams, resources, ideas and domains of influence.

This isn’t necessarily dysfunctional as psychological ownership can produce stewardship, responsibility and care.

But when organisational identity, status, reward and security become attached to possession, ownership can become defensive. Knowledge is withheld, boundaries are protected and collaboration becomes conditional.

This is why the ubiquitous executive injunction to “break down the silos” has always struck me as inadequate, too flimsly and easily dismissed with a polite “yes” in the room it is raised.

Silos are rarely demolished through exhortation because they are not simply attitudes. They are often rational adaptations to the architecture.

If someone’s organisational significance is partly communicated through the size of their budget, the number of people reporting to them, the decisions requiring their approval and the territory over which they exercise authority, asking that person to become radically non-territorial creates a profound contradiction.

We are asking people to surrender psychologically and politically what the organisational system continues to reward structurally.

The question therefore becomes less about persuading people to collaborate and more about designing organisations in which collaboration is the natural consequence of how work happens.

The organisation underneath the organisation

This is where Jon Husband’s concept of Wirearchy becomes especially valuable.

Wirearchy gives language to something most of us have experienced, but conventional organisation charts largely fail to capture: the dynamic networks through which knowledge, trust, credibility, influence and authority actually travel.

Every organisation has one.

The hierarchy might tell us that a decision should move from A to B to C, but experienced employees know that getting something done may involve speaking first to someone in Operations, checking an assumption with a former colleague now working in Technology, finding the analyst who understands the data, securing the confidence of someone who isn’t formally involved at all and only then entering the official decision-making process.

None of this appears on the organisation chart.

Yet much of the organisation’s actual intelligence resides there.

For decades we have treated these informal networks as supplementary to the “real” organisation. Perhaps we have that relationship backwards.

What if these relationships, connections and flows are not merely informal workarounds but glimpses of the organisational architecture we should have been designing for all along?

The significance of Wirearchy isn’t that hierarchy suddenly becomes unnecessary. Complex organisations still require accountability, coordination, institutional memory and clarity about certain decisions.

The more interesting proposition is that positional authority no longer adequately describes how agency operates.

Authority can travel.

A person can become highly influential because they possess relevant expertise, trusted relationships, or situational knowledge, then become less central when the context changes. Leadership can consequently become episodic rather than permanently attached to position. The network rearranges itself around the problem.

High-Reliability Organisation research offers an intriguing parallel through the idea often described as deference to expertise.

In environments where circumstances can change rapidly, and mistakes have serious consequences, the most useful knowledge may not reside with the most senior person. Expertise has to be allowed to become temporarily more important than rank.

This is not leaderless. It is something considerably more sophisticated: the intelligent movement of leadership towards where it is most useful.

And this is where Wirearchy begins to connect very directly with the Polymorphic Organisation.

From possessing authority to transmitting it

The traditional organisation tends to treat authority as something that resides somewhere. It belongs to a role, committee, function or level. We can delegate it, but even the language of delegation suggests that authority has an original owner who temporarily permits someone else to use it.

Networked organisations invite a different possibility. Authority might be understood less as a possession and more as a property of relationships: something activated through expertise, trust, context, legitimacy and participation.

This distinction matters because it changes what organisational leadership is for.

Instead of asking only, Who owns this decision?, we might ask, Where should this decision intelligently occur?

Instead of asking, Which function owns this capability?, we might ask, How can this capability move towards the problem that currently needs it?

Instead of asking, Who reports to whom?, we might become equally interested in Who needs to connect with whom for value to flow?

Those are not phrasing and semantic differences. They describe fundamentally different assumptions about organising.

They also suggest that the opposite of territoriality isn’t the absence of ownership. An organisation without ownership would rapidly become frustrating and irresponsible. Something which has set back many attempts at flat and self-managed organisations.

What we need instead may be a different quality of ownership: ownership as stewardship rather than possession. Something I’ve added into polymorphism time and again. In Polymorphic Organisations - Episode V (Who Leads?) here, stewardship is framed around three energies all linked to Incubation. And how leaders are there to incubate the whole and these important triadic energies/systems:

1. VC - The Capital System (what’s invested into the organisation and what it acquires)

2. OS - The Operating System (for the entire organisation - how it runs and serves its mission)

3. QG - The Energy System (an homage to QiGong - the Chinese ancient art of healing - the overall health and wellness of the people and the organisation)

Stewarding and incubating these three crucial elements of organisational work, flow and value creation are the critical elements of a Polymorphic Organisation and are not positions of power and control over everything. They are acting out the mission in a way that gives them stewardship over the past and present (legacy) and the future. An absolute cornerstone of polymorphism.

As a leader who stewards, you care deeply about something without preventing others from contributing to it.

• You can take responsibility for an outcome without constructing a permanent territory around it.

• You can exercise leadership intensely and then relinquish that leadership when another form of expertise becomes more relevant.

• You can belong strongly to a team while simultaneously participating in several networks across the organisation.

Ownership can remain strong while boundaries become porous. That is an important distinction that leaders who lean heavily into heroic efforts, don’t seem to recognise or desire.

Designing for flow rather than boxes

It also brings us back to the Operating Model conversations we all now seem to be engaged in. And rightly so as the very construct of Operating Models has become a ubiquitous consideration as AI comes into workflows and tears apart previously human operator tasks.

Perhaps one reason operating-model transformations so frequently disappoint is that we keep redesigning the flow into boxes when what actually needs redesigning are the flows between them.

We change reporting lines, consolidate functions, create centres of excellence, introduce business partners, establish new governance forums and redraw spans of control. Some of these interventions are entirely legitimate. But if information still travels badly, authority remains unnecessarily distant from the work, incentives reward local optimisation and people require political skill to mobilise capabilities across boundaries, we may simply have rearranged the visible architecture while leaving the deeper organisational logic untouched.

Some organisations already hint at alternatives.

Buurtzorg remains important not because everyone should copy its model - copying organisational forms is itself part of the problem - but because its self-managing nursing teams demonstrate what happens when the organisation is deliberately designed around the primary flow of value (in this case, the health of their patients not the statistics of the healthcare provider).

W. L. Gore’s lattice philosophy similarly challenges the assumption that relationships and influence need to follow conventional chains of command.

Haier’s evolution through RenDanHeYi offers another, very different attempt to break the monolithic enterprise into smaller entrepreneurial units connected more directly with users and market opportunities.

None of these are perfect examples of a “breakthrough for all”. None provide a universal template we can simply copy.

That may be precisely the point. The next organisational paradigm is unlikely to arrive as another best-practice model that everyone dutifully installs.

The Polymorphic possibility

This is increasingly where I locate the idea of the Polymorphic Organisation.

Polymorphism isn’t simply another word for agility, decentralisation or self-management. Nor is it a proposal to abolish structure. It starts from a different premise: that in conditions of sustained complexity, the organisation needs the capacity to change its form while retaining its coherence.

Teams may need to assemble and dissolve.

• Capabilities may need to migrate.

• Decision rights may need to move.

• Leadership may need to oscillate according to context.

• Proficiency may need to be combined in configurations that weren’t anticipated when the annual organisation chart was approved.

• Some organisational spaces may expand while others contract.

• Formal hierarchy may remain useful for one type of problem while a network, temporary mission team, community or autonomous unit becomes the appropriate form for another.

The organisation therefore stops searching for the perfect structure and develops instead an ability to structure itself repeatedly.

This is where I think Wirearchy and Polymorphism become particularly complementary.

1. Hierarchy tells us where formal authority has been located.

2. Wirearchy helps us understand how knowledge, influence and authority actually move through networks of human relationships.

3. Polymorphism asks whether the organisation itself can become sufficiently responsive to change shape around those flows.

That is a much more radical proposition than flattening the hierarchy.

It asks us to stop treating the organisation as an object that senior leaders periodically redesign and begin understanding it as a living system whose participants continually participate in its design.

And perhaps this is where our fascination with heroic leadership finally needs to give way.

The leader of the Polymorphic Organisation isn’t primarily the person who repeatedly rescues the enterprise from complexity. Their contribution may be almost the opposite: creating conditions in which intelligence can travel, expertise can become consequential, participation is meaningful, ownership is distributed without becoming ambiguous and people do not require extraordinary political dexterity merely to get sensible things done.

That requires a very different kind of executive team.

Not a collection of sovereign leaders arriving at the top table to represent Technology, People, Finance, Operations or Marketing, negotiating resources and defending the interests of their respective domains, but a group that understands itself as the temporary steward of the whole organisational system.

• Their expertise remains distinctive.

• Their accountability remains real.

• But their territory becomes porous.

And perhaps that is one of the deepest shifts required of leadership now: moving from protecting territory to stewarding flow.

Because the organisations capable of extraordinary things in the years ahead may not be those fortunate enough to employ an unusual number of heroic people. They may be the ones intelligent enough to notice where heroism has become compensation for bad design, curious enough to study the informal networks through which their people already make things happen, and courageous enough to redesign themselves around what they discover.

The ambition isn’t to remove human ingenuity from organisations. Quite the opposite.

It is to stop wasting so much of that ingenuity on overcoming the organisation itself.

Perhaps that is one of the simplest tests of a Polymorphic Organisation:

How much of the extraordinary capability of its people is spent creating value - and how much is still being spent navigating the system that was supposedly designed to help them do it and forcing, incentivising, encouraging or allowing them to be the wrong kinds of heroes?

What can we do to overcome the trap of the prevailing (and wrong) sort of Hero Leadership?

It would be tempting at this point to conclude that the answer to all of this is a wholesale reinvention of the organisation: dismantle the hierarchy, redistribute authority, reorganise around networks, introduce self-management and emerge, some months or years later, as a beautifully fluid Polymorphic Organisation.

I don’t think that is either realistic or particularly desirable.

Organisations contain histories, obligations, regulatory requirements, professional identities, technologies, contracts, governance arrangements and deeply embedded expectations about where authority resides.

Some hierarchies exist for very good reasons. Some decisions genuinely require concentrated accountability. And few organisations have the appetite, capability or necessity to redesign everything simultaneously.

Indeed, attempting to install Polymorphism as another transformation programme would rather spectacularly miss the point.

The more useful question is whether we can begin changing some of the conditions that produce territoriality, Heroic Debt and organisational friction without waiting for a new operating model to arrive.

I think we can.

We can start by becoming much more curious about where heroics are occurring.

Instead of simply celebrating the person who rescued the project, secured the approval, reconciled the functions or found the workaround, we might begin treating these moments as organisational data.

• What had to be overcome?

• Why was exceptional effort necessary?

• Which boundary prevented the work from flowing naturally?

• Where was information unavailable, authority misplaced or capability inaccessible?

This doesn’t diminish the person who intervened. It honours their contribution differently. Their ingenuity becomes an opportunity to improve the system rather than another reason to preserve it.

Imagine adding one question to every significant project review:

What did somebody have to do heroically that the organisation should have made ordinary?

Over time, the answers would reveal an extraordinary map of the organisation’s actual friction.

And from there, we might start designing some of it out.

Not through another grand restructuring, but through the steady removal of unnecessary organisational viscosity:

1. An approval no longer required; information made visible;

2. Two teams given permission to work directly together;

3. A decision moved closer to those possessing the relevant knowledge;

4. A budget shared around an outcome rather than guarded within a function;

5. A recurring meeting replaced by an accessible information flow;

6. Expertise made discoverable across the organisation rather than trapped within a department.

Small interventions perhaps, but ones that change the physics of work.

We can start designing for the organisation that already exists underneath itself.

Most organisations already possess something resembling Jon Husband’s aforementiond Wirearchy. aforementioned

People have networks of trust, credibility, knowledge and reciprocity through which they make things happen regardless of what the formal organisation chart suggests.

Instead of regarding those networks as informal and therefore somehow secondary, leaders could become genuinely interested in them.

• Who connects otherwise disconnected parts of the organisation?

• Where does expertise actually reside?

• Who do people approach when they need to understand something rather than merely have it approved?

• Where are the relationships through which difficult work becomes possible?

• Which people repeatedly act as bridges between professional, geographical or functional communities?

Network science has long distinguished between tightly bonded groups and the bridging connections that allow information and ideas to travel between them. Both matter. Strong internal relationships create trust and cohesion; bridging relationships prevent that cohesion from becoming enclosure.

We don’t therefore have to abolish departments to weaken departmentalism.

We can deliberately create more bridges.

Cross-functional missions, communities of practice, temporary problem-solving teams, internal talent marketplaces, peer networks, open strategy processes and more porous access to information can all begin changing the topology of an organisation without changing a single reporting line.

The hierarchy can remain.

We simply stop expecting it to carry all of the organisational intelligence.

We can allow authority to move occasionally

The same is true of leadership.

Few organisations need to move immediately towards radical decentralisation, but almost every organisation can experiment with allowing more decisions to occur where the richest knowledge resides.

Mary Parker Follett’s century-old idea of the law of the situation remains surprisingly radical here. Rather than endlessly asking who has authority over whom, we can focus on what the situation requires and whose knowledge is most relevant.

Sometimes that will still be the executive.

Sometimes it emphatically won’t.

This is where the idea that leadership should create more leaders becomes more interesting than simply distributing leadership development opportunities.

The task is not to persuade everybody to think of themselves as a leader. It is to create more legitimate places from which leadership can emerge.

• A project team can lead something.

• A community can lead something.

• A customer-facing colleague can lead something.

• A temporary coalition of expertise can lead something.

And when the situation changes, leadership can move again.

This is one of the smallest Polymorphic moves an organisation can make, because nothing necessarily changes on the organisation chart.

What changes is the assumption that authority must always travel vertically before action can travel horizontally.

We can change what executive teams believe they are there to represent

There is another intervention available at the very top of the organisation: Many executive teams are structurally assembled as a collection of territories.

The Finance leader brings Finance, the People leader brings People, the Technology leader brings Technology and the Operations leader brings Operations. Inevitably, part of their work becomes representing, negotiating and occasionally defending those domains.

What if the first obligation of an executive team were instead explicitly understood as stewardship of the whole system?

Functional expertise would remain indispensable, but functional sovereignty would not. That changes the questions around the table. Not:

• what does my function need? but what does the system need?

• whose budget should fund this? but where should capital move to create the greatest value?

• who owns this? but what configuration of capability does this problem require?

• which leader is accountable? but where should accountability sit for this particular phase of the work?

This isn’t semantics. Language reveals the mental model from which people are organising.

And changing that mental model costs remarkably little.

We can learn to attend to organisational energy

As a Chief Energy Officer, I would say that wouldn’t I?

But this is also where I think the Triadic Leadership Energies (from Chronicle V) become useful as a practical discipline rather than simply a model.

Borrowing loosely from the metaphor of Qigong, we can think of organisations not merely as structures but as systems through which different forms of energy have to circulate.

Capital Energy concerns what we are prepared and able to mobilise: investment, expenditure, acquisition, assets and resources.

Operating Energy concerns the organisational systems through which things become possible: workflows, technology, governance, decision architecture, structures, capabilities and coordination.

Human Energy concerns what makes participation possible and worthwhile: belonging, trust, inclusion, agency, meaning, relationships, psychological safety and the willingness to contribute.

The purpose isn’t to achieve some perfect equilibrium between the three. Living systems rarely remain in equilibrium.

It is to notice where energy is accumulating, where it is depleted and where it cannot flow.

• An organisation may possess Capital Energy but lack the Operating Energy required to translate investment into capability.

• It may possess beautifully engineered Operating Energy while Human Energy drains away through exhaustion, exclusion or loss of meaning.

• It may possess extraordinary Human Energy — committed, ingenious people who care deeply about the mission — but starve them of the Capital Energy required to make progress.

And this last condition should concern us particularly, because it is fertile ground for Heroic Debt.

People compensate.

They give more.

They improvise.

They absorb.

They carry the system’s deficiencies personally.

Eventually we praise their resilience when perhaps we should have questioned why so much resilience was required.

Systems leadership therefore becomes partly the practice of attending to these energetic conditions and asking not merely what must we do?, but what must be allowed to flow differently for this system to become more capable?

We’ve known about flow for a long time but perhaps not in this way.

We can redesign one flow rather than the whole organisation

Perhaps this is the most practical starting point of all.

Don’t redesign the organisation: Choose one important flow of value and follow it.

• Follow a customer request from beginning to end.

• Follow an investment decision.

• Follow an employee joining the organisation.

• Follow an idea from conception to implementation.

• Follow a piece of customer intelligence until it reaches somebody capable of acting upon it.

• Follow a strategic decision until it becomes different behaviour somewhere at the edge of the organisation.

And notice what happens along the way.

1. How many boundaries does it cross?

2. How often does it wait?

3. How many approvals are required?

4. How many times is information translated, reformatted or re-entered?

5. Where does ownership become ambiguous?

6. Where does somebody have to intervene?

7. Where does Human Energy drain away?

8. Where does Operating Energy create friction rather than movement?

9. Where is Capital Energy unavailable despite an obvious opportunity?

And, perhaps most revealingly, where does the formal organisation bear almost no resemblance to the way the work actually gets done?

Redesigning one flow teaches an organisation considerably more about Polymorphism than attending a seminar about future operating models ever could.

Because people experience what happens when structure becomes subordinate to value rather than value becoming subordinate to structure.

And we can change what we celebrate

Culture follows attention surprisingly closely.

If organisational stories continually celebrate the executive who intervened, the individual who worked all night, the team that endured impossible circumstances or the charismatic leader who personally drove the transformation, then heroism remains embedded in the mythology of success.

What if we became equally fascinated by the opposite stories?

• The leader whose team no longer needed them.

• The process that disappeared.

• The decision that moved three levels closer to the work.

• The team that shared its budget.

• The expert who gave away their knowledge until it ceased to confer special status.

• The executive who surrendered authority because somebody else understood the situation better.

• The cross-functional group that solved something without escalation.

• The person who removed the reason for their own organisational indispensability.

These are quieter stories.

They may also be the stories of much more sophisticated leadership.

Perhaps one of the deepest distinctions between heroic leadership and systems leadership concerns what remains after the leader’s intervention.

1. Heroic leadership asks us to notice what happened because the leader was there.

2. Systems leadership invites us to notice what can continue happening when they are not.

And Polymorphic leadership eventually asks something even more demanding: how many different configurations of intelligence, capability, authority and energy can this organisation generate without waiting for someone at the top to tell it what shape to take?

We don’t have to become fully Polymorphic tomorrow to begin finding out.

• We can map a flow.

• Remove a blockage.

• Move a decision.

• Open a boundary.

• Connect two previously separated communities.

• Share a resource.

• Notice a heroic workaround and eliminate the reason it was necessary.

• Examine whether Capital, Operating and Human Energies are circulating or becoming trapped.

• Give expertise temporary authority.

• Allow leadership to emerge somewhere unexpected.

None of these things requires a new organisation chart.

Collectively, however, they begin changing something much more important than the chart: the underlying logic through which the organisation understands itself.

Perhaps that is how organisations really begin to become Polymorphic anyway.

Not through a declaration that the transformation has begun, nor through the arrival of a beautifully illustrated target operating model, but through hundreds of deliberate acts that make the organisation slightly less territorial, slightly more porous, slightly more participative and considerably more capable of changing its own shape.

We don’t need to dismantle the organisation to begin.

We need to stop asking extraordinary people to compensate endlessly for ordinary design.

And start making extraordinary organisational capability an ordinary property of the system.

It is one of those phrases that has become so embedded in organisational life that few people stop to ask whether it is actually true, let alone whether Drucker said it.

Incidentally, what he DID say (in a Wall Street Journal article and in his book Management Challenges for the 21st Century) was this:

“Culture - no matter how defined - is singularly persistent.”

Mark Fields (former Ford CEO) apparently used the “...for breakfast” phrase or something like it.

Drucker’s core thinking appears to have been:

• Work with your culture, not against it: Drucker argued that trying to force a strategy that directly opposes an organisation’s deep-seated culture is a fool’s errand. Instead of trying to “fix” or overhaul culture from the top down, leaders must design strategies that leverage the existing culture’s strengths.
  

• Focus on habits, not “culture reform”: Drucker believed you cannot change culture directly by declaring new values. You can only change specific habits, tasks, and operational processes—and over time, the culture shifts as a byproduct.
  

• Execution over abstraction: Another closely related Drucker quote captures his view on strategy sitting on paper:

  “Plans are only good intentions unless they immediately degenerate into hard work.”

However, around culture, if you spend any time around leadership conferences, HR events or LinkedIn, you’ll hear familiar refrains.

• “We need to fix the culture.”

• “It’s all about behaviours.”

• “Employee engagement is falling.”

• “Purpose drives performance.”

• “People don’t leave organisations; they leave managers.”

Every few years a new phrase captures our imagination. We invent new frameworks, launch new initiatives, redesign competency models and rewrite our values in the hope that this time, somehow, things will finally change.

Sometimes they do. Often they don’t.

Recently I listened to Bruce Daisley’s excellent conversation with Professor Rob Briner about culture, behaviour and evidence.

As ever, Bruce approached the discussion as a thoughtful practitioner, interested in helping organisations become better places to work. Rob, meanwhile, did what Rob has built his reputation upon doing exceptionally well. He challenged assumptions. He dismantled fashionable ideas.

Rob questioned whether concepts like culture have become so broad and ill-defined that they have lost much of their practical usefulness. His argument was both simple and compelling.

• Perhaps organisations spend far too much time trying to change culture.

• Perhaps we should stop talking about culture altogether and focus instead on observable behaviours.

There is much to admire in that position: Behaviour is visible, can be measured and can be reinforced.

Culture, by comparison, often feels mysterious.

Organisations frequently talk about it as though it were an invisible force floating through the corridors, somehow responsible for everything from customer satisfaction to absenteeism.

Listening to the conversation, however, I found myself thinking that something even more fundamental was missing. Not because Bruce was wrong; nor because Rob was wrong. I tend to fixate a lot less than some about right/wrong and dichotomous frames.

Hence, my thinking here is that both thinking giants here were looking one level above where I started to feel that the really interesting questions begin.

The question isn’t whether culture matters. Nor is it whether behaviour matters.

The more important question is this: Where do behaviours actually come from?

A word that I keep seeing.

And it is a word we rarely use in organisations. Outside politics, it has almost disappeared from everyday language.

The word is sovereignty.

Mention sovereignty today, and many people immediately think of constitutions, monarchies, national borders or perhaps Brexit. The word carries political baggage. It sounds formal, distant and perhaps even slightly old-fashioned.

Which is unfortunate. Because beneath all that historical weight lies one of the most important ideas we could bring back into organisational life.

Sovereignty is the capacity to govern oneself.

Not selfishly or independently of everyone else, but with intentionality, responsibility and judgement.

• A sovereign nation determines its own future.

• A sovereign individual exercises meaningful agency over their own life.

Once we strip away the politics, the idea might feel somewhat surprisingly intimate. Perhaps the opposite of sovereignty isn’t oppression (as we’ve come to frame it). In organisational life at least, the opposite of sovereignty could be dependence.

That could significantly change how we perceive culture, behaviours, and their interrelationships causing engagement, toxicity and the other concepts many like to pull threads on like Psychological Safety, trust, resilience and a whole lot more. For now, we’ll stick with culture and behaviours (as much of the other things seem to stem from one or both of these elements).

When we look back, - over a century in the case of organisations - they have largely been designed around a simple assumption: The system thinks and people execute.

F W Taylor probably did not intend to create unhappy workplaces. He was trying to solve a problem of industrial productivity. The scientific management movement dramatically increased efficiency by separating planning from execution. Managers designed the work. Employees carried it out.

It worked brilliantly for factories. I think we can all say less brilliantly so for knowledge work in the 21st Century.

The irony is that while organisations have become immeasurably more sophisticated, many of their assumptions remain surprisingly similar.

• We recruit intelligent people; then we ask them to wait for approval.

• We encourage initiative; then surround it with dense layers of governance.

• We celebrate innovation;then measure compliance.

• We tell people to “act like owners” while reserving ownership of decisions for relatively few.

The language has evolved, and yet the operating system of work hasn’t.

Perhaps this explains one of the strangest paradoxes of modern work, in that so many organisations genuinely want things like entrepreneurial thinking and yet they continue to produce organisational dependency.

People become increasingly qualified, capable and using the most advanced tools known to humankind, but we’ve become progressively less sovereign.

This is why the work of the German philosopher Axel Honneth struck such a chord with me.

His recent book is called The Working Sovereign. The title alone feels quietly revolutionary as it’s not the engaged employee, the empowered colleague or even the high performer.

The working sovereign.

Honneth has spent decades developing what is known as the Theory of Recognition. His central proposition is that human freedom does not emerge in isolation. We become ourselves because other people recognise us. Recognition gives us identity. Identity gives us confidence. Confidence allows us to participate as free individuals within society.

Freedom (in Honneth’s context) is not simply the absence of control - it is the presence of recognition.

This feels like a profound distinction to me.

Many organisational initiatives pursue autonomy. Of course there are well-founded movements (Self-Management, Agile, Teal, Sociocracy, Holacracy, Humanocracy, Freedom at Work) that centre on autonomy. I’ve been in this “space” for over two decades now.

Very few of these enterprises and movements ever mention, talk about and therefore probably don’t cultivate sovereignty.

There is a big difference which isn’t just pedantic linguistic choices or labels:

• Autonomy asks whether I can choose how I complete my work - it is discretion and process

• Sovereignty asks whether I possess sufficient recognition, legitimacy and agency to shape the work itself. Authorship and purpose.

That distinction, I believe, has the potential to change the conversation completely.

Interestingly, psychology appears to have been pointing in this direction for decades.

I often quote Edward Deci and Richard Ryan’s Self-Determination Theory, which argues that human motivation depends upon three fundamental psychological needs.

• Autonomy.

• Competence.

• Relatedness.

We often quote autonomy because it fits neatly with modern ideas about flexible working and empowerment. But sovereignty integrates all three.

• Agency without competence produces anxiety.

• Competence without belonging produces isolation.

• Belonging without agency produces dependency.

Sovereignty emerges when all three begin working together.

• Albert Bandura’s work on self-efficacy reaches similar conclusions. Human beings behave differently when they believe they can influence outcomes.

• Amy Edmondson demonstrates that psychological safety enables people to contribute ideas without fear.

• Judith Glaser showed how trust changes the quality of collaboration through measurable neurological mechanisms.

• Martin Seligman’s work on flourishing repeatedly highlights meaning, accomplishment and agency.

Different disciplines and yet remarkably similar conclusions.

People thrive when they experience themselves as capable actors rather than managed objects.

Perhaps sovereignty has been hiding in plain sight all along.

Yet psychology alone is only half the story. To understand sovereignty properly we also need to understand development.

This is where Harvard Business School Professor Robert Kegan’s Adult Development Theory becomes extraordinarily helpful. Kegan’s work has fascinated me for years because it explains something every consultant, coach and leader eventually encounters.

Give two equally talented people the same degree of freedom in identical systems and circumstances. One flourishes and yet the other feels overwhelmed. Why is that?

The answer may not lie in capability - it may lie in consciousness..

Kegan’s work is a further build (in adults) on what Jean Piaget’s early 20th-century work with development was about children). Kegan’s positioning (and I’m probably grossly oversimplifying this) is: “How does the relationship between the self and the world continue to develop throughout adulthood?”

Kegan’s work therefore proposes that adults continue developing throughout life. One of the most important transitions and realisations is the movement from what he calls the Socialised Mind to the Self-Authoring Mind and, the possibility then of the Self-Transforming Mind.

Before we dive into this, I need to share something about “levels” based theories or conceptualisations.

Some readers may be cautious of developmental models that appear to place people on hierarchical ladders of consciousness. I share some of that caution. Human beings are far more contextual than any model can fully capture.

Rather than viewing sovereignty as a level to attain, I see it as a capacity that expands and contracts depending on our experience, our relationships and, crucially, the systems within which we work.

Organisation Design does not determine our maturity, but it can profoundly influence whether our more sovereign capacities are invited - or suppressed.

Think of Kegan’s descriptions of Adult Development not as a hierarchical ladder but as developmental capacities and capability repertoires.

Just as Professor Clare Graves did with his Emergent Cyclical Theory of Adult Human Biopsychosocial Systems Development humans can adapt, evolve, de-evolve and much of that is dependent on our situation, systems and context.

Anyway, back to this.

At the Socialised stage of Kegan’s work, our identity is largely shaped by external relationships. People seek guidance from accepted authorities. They ask, often unconsciously, “What is expected of me?”

There is nothing inherently wrong with this stage. Indeed, many successful people/professionals spend much of their careers operating here.

But genuine sovereignty remains elusive because authority still lives outside the self.

The individual looks outward before looking inward. The organisation becomes the source of certainty.

The Self-Authoring Mind represents a profound shift as people begin constructing their own internal operating system.

Instead of asking, “What do they want?“ they increasingly ask, “What do I believe?“

They become capable of challenging accepted wisdom. Holding values independent of group expectations. Making difficult decisions.Accepting responsibility for consequences.

In many respects this is the psychological birthplace of sovereignty.

It also explains why so many self-managed organisations encounter difficulties. They redesign structures around distributed authority but often assume everyone is psychologically prepared to inhabit them.Some are and some aren’t.

The problem is not intelligence, nor commitment - it looks more like it is developmental readiness.

So in more systems-like terms: Organisations frequently distribute sovereignty faster than people have developed the capacity to hold it.

That single observation may explain why some experiments in self-management flourish while others quietly recreate hierarchy under different names.

Kegan’s uppermost developmental stage, the Self-Transforming Mind, offers an even richer perspective. Here, individuals no longer cling rigidly even to their own worldview.

They become comfortable with paradox. Multiple truths, continuous learning and their identity appear to become more adaptive rather than fixed.

Reading Kegan (again) through the lens of Polymorphic Organisations is more striking for me now, than it was 5 years ago.

A Polymorphic Organisation changes form without losing coherence. A self-transforming individual changes perspective without losing identity.

Both become adaptive systems, whilst both retain purpose even as they evolve continuously. And both understand that certainty is less valuable than learning.

So one could presume that sovereignty itself also evolves.

At first we seek sovereignty over our own work. Eventually we seek stewardship of something larger than ourselves. This is where Honneth and Kegan (to my knowledge anyway) unexpectedly converge.

Many people imagine sovereignty as rugged individualism, complete independence and total self-sufficiency. I suspect that neither thinker (Honneth or Kegan) would agree.

For Honneth, freedom emerges through relationships of recognition.

For Kegan, the most developmentally mature individuals understand themselves as part of larger, interconnected systems.

Neither advocates isolation and both describe relational freedom. The sovereign individual is therefore not someone who doesn’t need anybody.

They are someone capable of participating fully without becoming psychologically dependent upon external authority.

That is a very different picture of leadership. And perhaps a far healthier one.

Why self-managed companies might struggle more than they have to

This also sheds fascinating light on the growing movement towards self-managed and self-organised organisations.

Over the past forty years we have seen remarkable experiments around the world.

• Semco

• Buurtzorg

• Morning Star

• W. L. Gore

• Haier

• AES

• Menlo Innovation

• Beetroot

• Mayden

Different sectors, different cultures and certainly different histories.

Yet remarkably similar assumptions: People are capable of considerably more responsibility than traditional management systems often allow.

These organisations are usually described as self-managed.I increasingly wonder whether that description is incomplete. Perhaps they are better understood as sovereignty-centred organisations.

Their real innovation is not the removal of managers (as we’re seeing in some of the tech bro-led giants). It is the redistribution of meaningful agency.

Authority migrates towards the point where value is created; leadership becomes contextual rather than position and trust becomes an operating principle rather than a leadership competency.

We’ve covered this before in Polymorphic Chronicles - Chronicle V - Who Leads? here

Leadership not just as positional roles but energies, and frames of incubation, activation and belonging/health.

In a system where meaningful agency is redistributed clearly and coherently, people stop waiting to be managed. They begin governing themselves together. Notice that last word I used there. Together. Because sovereignty should not - and does not - eliminate collective responsibility. It actually deepens it.

Which brings me back to Bruce Daisley and Professor Rob Briner.

Rob Briner is right to challenge organisations that use the word culture as a convenient explanation for almost everything. Too often it becomes a catch-all phrase that substitutes diagnosis with metaphor. If customer satisfaction falls, it must be culture. If innovation stalls, it must be culture. If engagement declines, it must be culture. Such explanations rarely help us understand what is actually happening.

Yet dismissing or abandoning culture altogether (or diminishing it considerably) would be an equally significant mistake. This is where I continue to find Stan Slap’s work enormously persuasive.

Stan argues that culture isn’t an abstract force floating around an organisation.

In a recent “paging” call I made to Stan on LinkedIn, here’s his response - which was specific to the post but rings true generally anyway.

“But to gain enterprise adoption for this thinking the argument can’t be that having a good culture is better than having a bad culture for ethereal reasons that are subordinate to measurable business performance.

Culture will rarely be considered a true priority by a company until it is inarguably linked to the metrics important to their key stakeholders.

Culture is where the humans gather in business. It’s only when the power of a culture’s commitment is positioned as a performance asset that a company will protect it, same as it will protect any such asset. This particular asset can’t be protected without protecting the humanity it represents, and without a company ultimately discovering or rediscovering its own humanity.

SLAP is my company and maximizing the commitment of a company’s culture is our exclusive focus. For over 30 years, in 44 countries, we have directly influenced billions of dollars in performance improvement for many of the world’s most demanding, successful companies.

That’s what we do. By doing it we make the business case for humanity, which is why we exist.”

Or as I’ve synthesised Stan’s work (probably really badly here): Culture is the collective expression of what people voluntarily choose to give of themselves.

Not what their contracts require. Not what their managers inspect. But what they willingly contribute because they believe it matters. That feels profoundly important, because voluntary contribution cannot be commanded - it can only be invited.

And I am of the belief that such an “invitation” depends upon something deeper still.

Sovereignty.

People who experience themselves as recognised, trusted and capable of exercising meaningful judgement tend to contribute more than compliance alone can ever produce.

Perhaps culture isn’t the starting point that many of us have come to believe though. My sense is, nor is behaviour.

Perhaps culture is what emerges when sovereign people repeatedly choose to act in service of something they genuinely believe belongs to them.

So likewise, Bruce is right to remind us that leaders still need language capable of describing collective experience. But perhaps the debate itself belongs to an older way of thinking.

Culture or behaviour? Maybe neither sits at the beginning of the story.

Behaviour does not emerge spontaneously and nor does culture. We can probably ALL agree on that.

Both emerge from something deeper.

Systems shape interactions. Interactions create experiences.Experiences influence identity. Identity shapes sovereignty. Sovereignty informs judgement. Judgement produces behaviour.Behaviour creates patterns.Patterns become what we eventually describe as culture.

Culture then reinforces the system.

It is not a hierarchy. It is a flywheel. And if you’re following this body of work on Polymorphism in organisations, you’ll know I’m with flywheels ALL the way. As performance architecture, momentum-building and sustaining loops of progressive performance.

And once we see the flywheel, we stop arguing about which single lever matters most.

We begin designing the entire system.

Deeper into Polymorphism

This, for me, is where the idea of the Polymorphic Organisation starts to reveal its deeper purpose.

Until now I have written about Spaces rather than Divisions, Proficiency Stacks, Organisational Oscillation, adaptive platforms and flywheels. These describe new organisational forms.

But forms alone are never enough.

Every organisation design quietly assumes something about human beings.

• Industrial organisations assumed people required supervision.

• Knowledge organisations assumed people required empowerment.

• Perhaps Polymorphic Organisations assume something different altogether.

They assume people can become sovereign.

Not immediately, not universally, certainly not perfectly. But progressively.

The purpose of Organisation Design therefore shifts.

We are no longer simply creating better structures; we are creating developmental environments in which sovereignty can grow.

• Recognition becomes more intentional.

• Capability becomes more visible.

• Authority becomes more contextual.

• Learning becomes continuous.

• Power becomes dynamic rather than fixed.

The organisation itself becomes less like a machine and more like an ecology. Not merely producing outputs, producing sovereign human beings.

Perhaps this is the conversation waiting beyond engagement.

Beyond empowerment, beyond culture, and beyond behaviour.

Those ideas remain useful, but they are no longer the destination.They are stepping stones towards something more fundamental.

For decades we have asked how organisations can become more productive. Then we asked how they could become more engaging. More recently we have asked how they might become more adaptive.

The next question may simply be this.

How do organisations help people become capable of governing themselves wisely in service of something larger than themselves?

That, to me, is the question of sovereignty. And perhaps it is also the question that sits quietly beneath every Polymorphic Organisation.

Not how we build more flexible systems, not how we create stronger cultures and not even how we develop better leaders. But how we cultivate people capable of exercising wise judgement, sharing responsibility, shaping systems and continually adapting together.

Because when people become sovereign, better decisions emerge.

When better decisions emerge, healthier behaviours follow. When healthier behaviours become habitual, stronger cultures naturally develop. And when organisations learn to cultivate sovereignty rather than simply manage performance, they do something rather extraordinary.

They stop producing compliant employees. They start producing citizens of work.

Working sovereigns.

Perhaps that’s the future we’ve been searching for all along?

Bruce and Rob’s podcast episode is found here:
https://eatsleepworkrepeat.com/stop-talking-about-culture-deal-with-behaviours/

We often speak of tokens as though they are something new, but they are most certainly not.

Money itself is merely a socially accepted token. It possesses value because we collectively agree that it does.

Organisations are, in many respects, token systems too.

• Salaries are tokens exchanged for capability.

• Bonuses are tokens exchanged for performance.

• Equity is a token representing future value.

• Even reputation may be thought of as a social token, accumulated slowly and spent carefully.

What may be changing in the age of Artificial Intelligence is not the existence of tokens, but their granularity.

For perhaps the first time, knowledge work itself is becoming tokenised. Intelligence can now be bought, consumed and measured in microscopic units.A prompt has a cost.

An agent has a cost. A workflow has a cost.

The economics of work are becoming increasingly atomic.

And once work can be atomised, it can also be decomposed, recombined and reorganised.

This may prove to be one of the most profound organisational shifts of the twenty-first century.

Historically, money tokenised value. AI may now be: tokenising capability itself.

The progression almost becomes:

And perhaps by 2046 organisations become systems for allocating human, machine and relational tokens in pursuit of value creation.

We have long assumed organisations employ people.

Perhaps organisations are actually mechanisms for converting different forms of tokens into value. The question for leaders is no longer simply how much labour costs.

It is how different forms of tokens - human, computational, relational and symbolic - can be orchestrated into systems capable not merely of productivity, but prosperity.

Tokens and Polymorphic Organisations

The Polymorphic Organisation exists as both a concept and an actualisation approach to decouple us from rigid, static, stuck, and calcified approaches to work.

That work is now calling us to do something very different in how we approach the value equation and calls into question these two crucial frames:

1. How much are people worth? And in particular their skills, capabilities, endeavours, efforts, imagination, stamina, connectedness and sensing.
   

2. How much are machines worth? And in particular their accuracy, speed, reliability, consistency, certainty, clarity and replicability.

Only in the Agricultural shift to Industrial methods have we seen how much a plough, pesticides and fertilisers, a combine harvester and a sophisticated irrigation system, create value over humans.

Machines took over as the most prolific, reliable and predictable way to farm and then produce in factories and mills. We’re now seeing something similar in knowledge work.

It is not AI itself. Nor is it automation, agents, digital labour or even the increasingly breathless discourse surrounding Artificial General Intelligence. Those are important developments, but they are perhaps symptoms of something deeper.

A new economic logic might be emerging.

For over two centuries, organisations have largely been built upon that relatively simple equation: People sold time, energy and capability to organisations, in exchange for security and remuneration.

Work was packaged into jobs, jobs were grouped into functions, functions were arranged into hierarchies and hierarchies became organisations.

The industrial age created the architecture of employment that most of us still inhabit.

Yet every so often, a small change in economic mechanics creates an entirely new organisational paradigm.

Cloud computing changed how we thought about infrastructure. Streaming changed how we thought about ownership. Platforms changed how we thought about markets.

Artificial Intelligence may be doing something equally profound to work itself.

Increasingly, intelligence is being bought and consumed not through jobs or subscriptions but through tokens.

At first glance, this appears to be little more than a commercial pricing model.

OpenAI and Anthropic charge for tokens. Organisations building products through tools such as Lovable, Replit, Cursor or agentic workflows quickly become familiar with the economics of usage. Every prompt, every API call, every orchestration consumes computational resources that carry a measurable cost.

You pay for what you use.

Simple enough.

Yet hidden inside this seemingly innocuous mechanism is an entirely different way of conceptualising work.

For perhaps the first time in history, knowledge work is becoming economically atomic.

It can be measured, disaggregated and recombined in ways that were previously impossible.

This could change everything.

From Labour to Knowledge to Tokens

The history of organising can perhaps be understood through successive units of value.

The industrial organisation was built around labour, where the central question was straightforward: “How many people do we need?”

The knowledge organisation shifted attention towards expertise and the question became: “What capabilities do we require?”

Increasingly, however, organisations may be moving towards a different question altogether: “What combination of human capability, machine intelligence and computational expenditure produces the greatest value?”

This may sound subtle. It is not, because once work becomes measurable in smaller units, organisations will cease to think primarily in terms of jobs and begin to think in terms of these economic atoms.

• A legal review becomes an allocation problem.

• A piece of software becomes an allocation problem.

• A marketing campaign becomes an allocation problem.

Allocation problem meaning: Should this be done by humans? By AI? By some combination of both?

How much computational expenditure is justified? What is the relationship between quality, speed and cost?

These are not simply technological questions. They are fundamental organisation design questions.

Indeed, they may become some of the defining organisational questions of the next decade.

The Great AI Miscalculation

The last two years have already produced an interesting pattern.

A number of organisations announced significant reductions in engineering and knowledge roles on the assumption that AI would dramatically reduce labour requirements.

The story was simple: Fewer people. More AI = Greater efficiency.

Yet reality has proved rather more complicated.

Developers use AI extensively. Organisations purchase increasing quantities of tokens and computational services. New governance challenges emerge. Quality assurance requirements increase.

Architectural thinking becomes more valuable. Human coordination does not disappear.

In some cases, organisations have discovered that replacing labour costs with computational costs simply moves expenditure from one ledger to another.

The cost did not vanish; it changed form.

This is perhaps one of the first great misconceptions of the AI era. AI does not necessarily eliminate labour. Rather, it converts certain forms of labour into computational expenditure.

This is profoundly important because it means organisations are not entering an age of costless abundance.

They are entering an age of new economic trade-offs. And whenever trade-offs emerge, organisational form changes.

The Emergence of Economic Atoms

Historically, organisations have hidden enormous inefficiencies because work was difficult to measure.

• Meetings consumed time, but their costs were diffuse.

• Poor decision-making carried consequences, but these remained largely invisible.

• Rework, duplication and organisational friction were accepted as unavoidable features of corporate life.

Tokenisation begins to expose these hidden dynamics.

A poorly designed prompt architecture has a cost. An inefficient workflow has a cost. A redundant process has a cost. A badly orchestrated ecosystem of agents has a cost.

The organisation becomes increasingly visible as a system of economic flows.

In earlier Polymorphic Chronicles, I explored the idea that organisations are becoming more fluid, more platform-like and increasingly organised around capabilities rather than static structures.

This development adds another layer.

Not only could organisations become polymorphic in form, they may increasingly become polymorphic in economics.

Different organisational configurations will carry different token costs, as do different combinations of humans, AI and ecosystems - they will inevitably produce different value profiles.

The future organisation may therefore become less like a machine and more like an adaptive portfolio.

This aligns closely with ideas explored in:

• Polymorphic Organisations and Platform Thinking

• Spaces Not Divisions

• The Rise of Proficiency Stacks

• Organisational Oscillation

(all available in past Chronicles).

These earlier chronicles argued that organisational value increasingly emerges through dynamic recombination.

Tokenisation may provide the economic mechanism through which such recombination becomes possible.

Why Jobs Begin to Matter Less

Jobs have always been convenient containers as they bundle together activities that may or may not naturally belong together.

A marketing manager might undertake strategic planning, stakeholder engagement, copy review, budgeting, coaching and administrative work despite these activities requiring entirely different capabilities.

AI begins to separate these bundles.

Certain activities become highly automatable and others become augmented. Still others become even more deeply human. The result is not necessarily the end of work.

But it may represent the gradual unbundling of jobs.

This should sound familiar. Because the Skills-Based Organisation movement has already been moving in this direction.

John Boudreau and Ravin Jesuthasan have long argued that work should be deconstructed into tasks and capabilities rather than inherited job descriptions.

Tokenisation extends this thinking further. It asks not simply: “What skills are required?” more it invites us to think: “What is the most effective economic allocation of those skills?”

The unit of analysis shifts again.

People increasingly become portfolios of proficiencies.

Organisations become portfolios of capability deployment.

The New Importance of Capability Density

One of the more fascinating implications concerns the value of broad capability.

Individuals who combine systems thinking, facilitation, AI fluency, behavioural science, strategic sense-making, and relationship-building may become significantly more valuable than narrowly specialised experts.

Why?

Because they generate disproportionate value relative to computational expenditure.

They know where AI should be used. and where it should not, they reduce waste. and they orchestrate complexity and they improve system effectiveness so that their contribution extends beyond direct output.

In this sense, the future may belong less to specialists and more to organisational conductors: People capable of orchestrating human and machine systems.

This aligns strongly with ideas within the Polymorphic Organisation around Proficiency Stacks and developmental capability.

The question may increasingly become: “How much value can this individual unlock across the wider system?” - rather than: “How many outputs do they personally produce?”

There is a danger here and we’re already seeing it:

The Danger of Neo-Taylorism

A potentially darker possibility.

Every economic innovation carries shadow consequences. The industrial age gave us scale and prosperity. It also gave us Taylorism.

The knowledge economy gave us autonomy and creativity. It also gave us burnout and hyper-individualism.

The tokenisation of work may similarly produce its own distortions.

If poorly applied, organisations could become obsessed with measurement. Every interaction becomes quantified. Every contribution becomes scored and every activity becomes economically visible.

Humans become endpoints in a computational system.

A strategic insight becomes a unit of production and a coaching conversation becomes an inefficiency. Relationship building becomes difficult to justify because its value is diffuse and delayed.

This would represent a new form of digital Taylorism. A world where the immeasurable becomes undervalued simply because it resists tokenisation.

This would be deeply problematic, because some of the most valuable aspects of organisational life are precisely those things that cannot easily be measured.

• Trust.

• Meaning.

• Belonging.

• Judgement.

• Wisdom.

• Care.

• Stewardship.

These are not inefficiencies; they are often the conditions through which all other forms of value emerge.

A polymorphic perspective therefore requires us to resist the temptation to reduce organisational life solely to computational economics.

The future organisation cannot simply become an accounting system for tokens.

It must remain a human system.

Human Tokens and Meaning Tokens

Perhaps this is where we need to think differently.

Not all tokens are computational; some are relational, developmental and symbolic.

Every organisation runs upon invisible economies.

• Trust is a form of currency.

• Psychological safety is a form of currency.

• Reputation is a form of currency.

• Purpose itself may be understood as a form of currency.

Leaders spend and accumulate these currencies every day. Teams generate and deplete them and cultures amplify or diminish them.

The challenge therefore becomes one of orchestration.

• How do organisations combine different forms of value?

• How do they balance computational efficiency with human flourishing?

• How do they ensure that automation does not undermine meaning?

This feels increasingly relevant to the Human Economic Manifesto.

Because if prosperity is understood through human, social, intellectual, material, natural, and financial lenses, then tokenisation cannot be viewed merely in terms of financial efficiency.

It must also be examined through the broader ecology of value creation.

Organisational Oscillation and Token Economies

Another fascinating implication concerns organisational oscillation. Earlier chronicles proposed that future organisations may alternate between periods of expansion and consolidation.

Token economics may accelerate this tendency. During exploratory periods, organisations may increase human investment: Experimentation, creativity and relational work become more important.

During consolidation periods, greater automation and computational leverage may emerge.

The organisation continually recalibrates.

• Human.

• Machine.

• Ecosystem.

• Platform.

• Community.

This constant reconfiguration feels inherently polymorphic as organisational form becomes contingent rather than fixed. Different shapes emerge according to context and different economics produce different structures.

The organisation ceases to be a stable object. It becomes a living system of dynamic allocation.

Towards the Tokenised Enterprise

We may therefore be approaching a genuinely new organisational paradigm.

Not post-human.

Not fully automated.

But almost certainly post-job.

An enterprise where work is continuously decomposed and recomposed and where capability flows across boundaries. Where computational resources are strategically allocated. Where ecosystems contribute alongside employees. Where organisational forms continuously adapt.

In such a world, hierarchy may matter less than orchestration just as ownership may matter less than access. Even employment may matter less than contribution.

This is not the end of organisations, though.

It may, however, represent the end of many assumptions about how organisations should be designed.

The challenge for leaders is therefore not simply to adopt AI. Nor is it merely to reduce costs. The challenge is to understand the new economics that AI introduces.

Because every major technological shift eventually creates new organisational forms.

Steam produced factories.

Electricity produced corporations.

The internet produced platforms.

Artificial Intelligence may produce tokenised organisations.

The question is whether these become extractive systems of measurement and surveillance. Or whether they become adaptive, human-centred ecosystems capable of creating prosperity in richer and more meaningful ways.

My suspicion is that the answer lies not in automation itself.

But in polymorphism.

In organisations capable of continually reshaping themselves around changing contexts, changing economics and changing human needs.

The future may not belong to organisations that replace people with machines.

Nor to those that ignore technological possibility.

It may belong to organisations capable of orchestrating humans, machines and ecosystems as complementary sources of value.

In other words, organisations that understand that the tokenisation of work is not simply an economic development.

It is an organisational one.

And perhaps, quietly and almost invisibly, one of the most significant shifts in the history of management itself.

Looking Towards 2046: Six Glimpses of the Tokenised Organisation

The future rarely arrives all at once.

It tends to emerge unevenly, quietly and in fragments. The tokenisation of work may prove no different.

By 2046, organisations may not literally pay people in tokens nor operate as giant digital marketplaces for labour. Rather, tokenisation may become an invisible organising principle; a new economic grammar through which decisions about work, capability and value are made.

Some early signs are already visible today.

• Cloud computing transformed infrastructure from ownership to consumption.

• Software became “as-a-service”.

• Artificial intelligence is increasingly becoming “intelligence-as-a-service”.

Work itself may become similarly reconfigured.

Below are six possible glimpses into how this future could unfold.

Technology: The Computational Enterprise

A global software company in 2046 employs only half the number of people it did twenty years earlier. Yet it delivers four times the output. Not because humans disappeared, but because organisational boundaries dissolved.

Engineering teams now consist of:

• human architects,

• specialist AI agents,

• open-source communities,

• autonomous testing ecosystems,

• synthetic design partners,

• independent capability contributors.

Quarterly reviews no longer examine simply labour costs.

They review:

• human expenditure,

• computational expenditure,

• ecosystem expenditure,

• orchestration efficiency.

One team may consume millions of AI tokens each month and generate modest returns. Another may consume comparatively little computational capacity whilst generating enormous customer value.

The strategic question therefore changes.

Not: “How many engineers do we need?” more: “What combination of human judgement and computational intelligence creates the greatest value?”

The most valuable employees are not necessarily coders. They are conductors.

People capable of orchestrating humans and machines into coherent systems.

Government: The Citizen Resolution Economy

By 2046, governments no longer organise public services around departments alone. Instead, they increasingly focus upon outcomes. Housing, social care, education and employment services become integrated around citizen journeys.

A housing application may involve:

• AI document review,

• predictive vulnerability assessments,

• digital case agents,

• local community networks,

• specialist human intervention.

Routine administration becomes almost entirely computational, yet governments quickly learn an uncomfortable lesson: Efficiency and humanity are not always synonymous.

Citizens facing homelessness, addiction, bereavement or domestic abuse often require something machines struggle to provide presence, trust and understanding.

As a result, governments establish what become known as Human Sovereignty Zones.

Areas of public service where human engagement is intentionally prioritised, even where it appears economically inefficient.

Political debates shift accordingly and questions of public spending increasingly become questions of societal value: “What should never be tokenised?”

Retail: The Human Premium Economy

Retail perhaps undergoes one of the most curious reversals as by 2046, almost every transactional element of retail is computational.

Inventory management, merchandising, dynamic pricing, forecasting and personalised recommendation are all orchestrated by agents.

Consumers can buy almost anything instantly. Paradoxically, human interaction therefore becomes scarce. And scarcity creates value. Physical stores evolve into social and experiential environments.

Employees become:

• trusted curators,

• community hosts,

• style advisers,

• storytellers.

Customers willingly pay premiums for human interaction because it becomes differentiated.

The lesson for organisations becomes profound: As machines become abundant, humanity becomes premium.

The economic value of relational capability increases rather than declines.

Logistics: The Living Supply Network

Global logistics systems in 2046 resemble living organisms more than corporations.

Millions of autonomous decisions occur every second, as routes recalculate themselves and warehouses reorganise themselves.

Supply chains continuously adapt to geopolitical events, climate disruptions and customer demand, and entire organisational ecosystems become dynamically reconfigured.

Yet repeated crises reveal something important: Systems optimised purely for efficiency become dangerously fragile. Extreme optimisation produces brittleness.

Consequently, organisations begin intentionally investing in what earlier generations might have called inefficiency:

• redundancy,

• human oversight,

• local knowledge,

• slack capacity,

• trusted relationships.

Resilience itself becomes a strategic token and a new organisational metric emerges: Adaptive Capacity Per Token Spent.

The most valuable systems are not the cheapest. They are those capable of recovering fastest.

Healthcare: The Economics of Presence

Healthcare may become one of the first sectors to explicitly reject pure token economics.

By 2046:

• diagnosis is heavily AI-assisted,

• treatment plans are dynamically generated,

• administrative tasks are largely automated,

• predictive medicine becomes commonplace.

Yet patient outcomes repeatedly demonstrate something deeply human.

People heal better when they feel seen. Compassion influences adherence as trust influences recovery.

Presence influences wellbeing and Healthcare leaders increasingly speak about: Presence Capital: The value created through human attention, care and relational continuity. Consequently, some areas of medicine deliberately become protected spaces:

• palliative care,

• mental health,

• end-of-life support,

• complex case navigation.

Here, efficiency is not the primary objective: Human flourishing is.

Healthcare therefore becomes one of the first industries to formally recognise that not all value can be computationally measured.

Education: The Developmental Institution

Education may experience perhaps the greatest identity crisis.

By 2046, personalised AI tutors are universal. Knowledge becomes abundant. Lectures become largely obsolete. Content generation costs approach zero.

Educational institutions therefore confront an uncomfortable question:

“If information is free, what are schools and universities for?”

Their answer gradually becomes clear.

Development. Identity. Judgement. Citizenship. Meaning-making.

Educational institutions increasingly become places where people learn how to think rather than what to think.

Teachers become:

• developmental guides,

• coaches,

• facilitators,

• community builders.

Universities increasingly measure:

• curiosity,

• collaboration,

• ethical reasoning,

• systems thinking,

• developmental maturity.

The irony is remarkable: The more knowledge becomes computationally abundant, the more valuable human wisdom becomes.

The Tokenised Polymorphic Organisation

These examples may appear speculative, yet their foundations already exist.

Token expenditure is already replacing certain forms of labour expenditure and AI agents are already becoming collaborators. Work in this new “space” is already becoming decomposed into tasks, capabilities and allocative decisions.

The tokenisation of work therefore may not arrive through (televised) revolution.

It may arrive gradually, quietly and almost invisibly.

Until organisations eventually realise they no longer think primarily in terms of jobs or functions. Instead, they think in terms of:

• capabilities,

• ecosystems,

• contribution,

• orchestration,

• value allocation/creation

At that point, the Polymorphic Organisation becomes not simply an interesting design philosophy. It becomes a practical necessity.

Because if work is increasingly recombined at atomic levels, organisations themselves must become capable of continual recombination. The future may not belong to the most efficient organisations, nor to the most automated.

It may belong to those capable of deciding wisely what should be automated and what should remain deeply human. And how both can continually evolve together.

That may ultimately be the central leadership challenge of the next twenty years.

Not managing people, nor managing AI.

But managing the economics of humanity itself.

I say “generally,” with an emphasis on the CPO, given the current rhetoric denouncing HR as the “pantomime villains” of corporate life.

What strikes me about much of the criticism currently aimed at HR is that it is arguing with a version of the profession that is already beginning to disappear.

The debate often assumes that the future Chief People Officer will be some enhanced version of the HR Director. More commercial, perhaps. More data literate. Better at strategy. Better at influencing the board.

That may be true, but I sense and see (therefore more than suspect) something more profound is happening.

The organisations emerging into the next decade will not simply require better HR leaders: They will require enterprise architects.

And some of those architects will come from the people profession.

The reason is relatively obvious and even simple to frame: The challenges facing organisations today increasingly sit in the spaces between things. So between:

• strategy and execution

• technology and humanity

• capability and performance

• culture and structure

• leadership and governance; and

• adaptation and stability.

More paradoxes than polarities. More “and” than “or” and definitely are going to become more pressing and challenging for decision makers to compute and act upon.

Traditional executive leadership roles were designed for a world in which these domains could be separated and optimised independently. Most organisations still operate as collections of specialist functions connected by governance processes and periodic collaboration.

Yet complexity does not respect organisational charts.

• Artificial Intelligence does not arrive as a purely technology issue. It becomes a workforce issue, a capability issue, a leadership issue, a redesign issue and ultimately a strategic issue.

• Culture does not emerge from value statements. It emerges from operating models, decision rights, incentives, information flows and power structures.

• Engagement does not emerge from wellbeing programmes. It emerges from meaningful work, trusted leadership, intelligent design and human agency.

Increasingly, organisational outcomes are produced by interactions rather than interventions.

This is where the Enterprise CPO becomes interesting. Not because they “own” people, but because they understand systems.

The strongest people leaders I encounter today are often among the few executives capable of connecting these interactions together. They can see how a technology decision affects capability. And how:

• Capability affects performance

• Performance affects culture

• Culture affects adaptability

• Adaptability affects strategy; and

• How strategy eventually determines whether the enterprise survives.

That is no longer HR. That is enterprise stewardship.

In many ways, the Enterprise CPO is becoming the executive most naturally suited to helping organisations move towards a Polymorphic state.

A Polymorphic Organisation is not simply an organisation with flexible working or flatter structures. As I’ve set out across the 30+ chronicles before this, it is an enterprise designed to change shape intentionally. It possesses the ability to shift form, redistribute authority, reassemble capability and adapt leadership energy according to context.

• Rather than treating organisational structure as fixed, it treats structure as adaptive.

• Rather than treating leadership as positional, it treats leadership as contextual.

• Rather than treating jobs as permanent containers, it treats work as fluid combinations of skills, capabilities and outcomes.

This demands a fundamentally different form of leadership. The traditional executive seeks control. the Polymorphic executive seeks adaptability. The traditional executive protects territory, the Polymorphic executive cultivates flow. The traditional executive optimises a function, the Polymorphic executive optimises the system.

This is why Enterprise Leadership matters as not just a rebadging of the leader role; but an entire mindset, strategy, tactics, skills and learning shift in themselves. Because Polymorphism without enterprise thinking could quickly become chaos.

Someone must still

• hold coherence

• understand how value is created across the whole system and

• connect strategy, capability, technology, culture and performance into a coherent organisational narrative.

Increasingly, that responsibility is falling to the Enterprise CPO. Not alone, but alongside a similarly evolved CEO.

The most exciting CEO-CPO partnerships I am seeing today resemble less the traditional Chief Executive-HR Director relationship and more that of organisational architects.

The CEO focuses externally and systemically whilst the Enterprise CPO focuses internally and systemically.

• Together, they become stewards of organisational adaptability and create the conditions within which intelligence can distribute itself.

• Together they shape systems where authority can move to expertise as they reduce dependency on heroic forms of over-indexed, compression-chamber leadership.

• Together they design organisations capable of learning faster than the environments around them change.

And that, perhaps, is the greatest shift of all.

For decades, we have asked how HR can become more strategic.

The more interesting question now is whether the Chief People Officer becomes one of the principal designers of the adaptive enterprise.

Because if organisations genuinely are becoming more fluid, more skills-based, more AI-enabled, more networked and more complex, then somebody must understand how all those forces interact.

The Enterprise CPO may prove to be the executive role best positioned to do exactly that.

Why Enterprise Leadership Is Emerging Now

The rise of Enterprise Leadership is not happening because somebody has invented a new executive buzzword. It is emerging because the conditions surrounding organisations have fundamentally changed.

For much of the twentieth century, organisations were designed according to principles that made perfect sense at the time. Work was relatively predictable. Information moved slowly. Expertise sat inside professional silos. Planning cycles could stretch across years. Organisational structures were largely optimised for efficiency, consistency and control.

The assumptions underpinning those designs have been steadily eroding for decades.

Peter Senge warned of this in The Fifth Discipline, arguing that organisations increasingly suffer the consequences of fragmented thinking. Leaders optimise individual components whilst failing to understand the behaviour of the whole system.

Russell Ackoff made a similar observation, noting that improving the performance of individual parts rarely improves the performance of the whole. In many cases, it makes matters worse.

W Edwards Deming perhaps articulated it most clearly when he observed that a bad system will defeat a good person every time.

These are not merely philosophical observations.

Modern organisational research continues to validate them.

Deloitte’s Human Capital Trends reports have repeatedly identified that the most successful organisations are increasingly organised around networks, ecosystems, capabilities and teams rather than rigid functional hierarchies.

The Centre for Creative Leadership describes Enterprise Leaders as individuals capable of balancing organisational priorities beyond their own domain, creating value across boundaries rather than within them.

Russell Reynolds Associates has similarly highlighted that future executive success depends less upon functional expertise and more upon enterprise stewardship, systems awareness and organisational adaptability.

The evidence increasingly points in the same direction: The higher leaders rise, the less important their functional expertise becomes and the more important their ability to understand interactions.

That observation is particularly relevant for Chief People Officers. Because people leaders sit at a unique intersection of organisational life. They see where:

• Strategy collides with reality.

• Leadership behaviour shapes culture.

• Capability constraints undermine execution.

• Where governance creates friction.

• Where Organisation Design distorts performance.

In many ways, they have always had one of the clearest views of the enterprise system. The difference today is that organisations increasingly need someone to act upon those observations. Not merely report them.

The Shift from Jobs to Capabilities

One of the strongest signals supporting the emergence of Enterprise Leadership is the rapid growth of skills- and capability-based organisations.

For over a century, organisations have largely been designed around jobs.

• Jobs created Departments.

• Departments created hierarchies.

• Hierarchies created careers.

• Careers created management structures.

The model was logical when work changed relatively slowly.It becomes problematic when work changes continuously.

John Boudreau and Ravin Jesuthasan have spent more than a decade arguing that organisations should move beyond jobs towards work, skills and capabilities as the fundamental unit of organisational design. Increasingly we are seeing evidence of exactly that shift.

• Unilever has developed internal talent marketplaces that allow capability to move towards opportunities rather than remain trapped inside organisational silos.

• Schneider Electric has adopted similar approaches to workforce mobility and skills deployment.

• Gloat, SkyHive and other workforce intelligence platforms have emerged specifically because organisations recognise that future value creation depends less upon fixed structures and more upon fluid capability deployment.

These developments are often described as talent innovations.I think they are actually organisational innovations.

They represent early indicators of a Polymorphic future.

• When capability becomes more fluid, authority must become more fluid.

• When authority becomes more fluid, leadership becomes more contextual.

• When leadership becomes more contextual, organisations require executives capable of stewarding adaptability rather than preserving structure.

That is Enterprise Leadership.

And it is precisely why the future Chief People Officer may become one of the central figures in organisational evolution.

The Organisations Already Living This Future

Critics may argue that these ideas sound attractive but remain theoretical.

Yet examples already exist.

Haier’s RenDanHeYi model has spent years dismantling traditional bureaucracy in favour of entrepreneurial micro-enterprises capable of rapidly reconfiguring around opportunities.

Buurtzorg transformed community healthcare in the Netherlands through highly autonomous self-managing teams that dramatically reduced bureaucracy whilst improving outcomes.

Microsoft’s transformation under Satya Nadella involved a profound shift away from internal competition and towards learning, collaboration and systems thinking.

Even Spotify’s famous approach to squads, tribes and networks reflected an attempt to create greater organisational adaptability through modular structures rather than fixed hierarchies.

None of these organisations are identical.None offer a perfect blueprint. Yet they reveal a common pattern: The most adaptive organisations increasingly distribute intelligence, decentralise decision-making and create mechanisms through which capability can move more freely.

What they require from leadership is not greater control, they require greater coherence.

The role of leadership shifts from directing activity towards shaping conditions.

This is precisely the terrain where Enterprise CPOs can create disproportionate value, because organisational conditions have always been their domain.

• Culture.

• Capability.

• Leadership.

• Collaboration.

• Work design.

• Learning.

• Decision-making.

These are not solely HR topics, they are the building blocks of organisational effectiveness.

Why AI Makes This Urgent

Artificial intelligence is accelerating this transition dramatically.

The dominant narrative suggests AI is primarily a technology challenge.I believe that framing misses the point.

AI is exposing organisational design weaknesses that previously remained hidden.It reveals

• Duplicated work.

• Fragmented processes.

• Decision bottlenecks.

• Capability gaps.

• Managerial overload.

• Poor information flows.

• Weak knowledge management.

In many cases organisations discover they do not have an AI challenge at all.

They have a work design challenge.

Josh Bersin’s recent work on Systemic HR and Superworkers points towards exactly this conclusion. The organisations creating advantage through AI are not merely deploying tools: They are redesigning work itself.

McKinsey research similarly suggests that technology alone rarely creates transformational value. The greatest gains emerge when organisations redesign operating models, workflows, capabilities, and behaviours alongside the implementation of technology.

This matters because redesign is not owned by any traditional executive function.It sits between functions.

Which means somebody must orchestrate the whole. Somebody must understand how work, people, technology and performance interact. Increasingly that person is likely - and in some cases becoming - the Enterprise CPO.

Not because HR owns AI.

Because AI exposes the enterprise system.

And systems are becoming the true arena of competitive advantage.

The organisations that thrive over the next decade will not be those possessing the most advanced technology. Nor those possessing the strongest hierarchy. Nor even those possessing the smartest leaders.

They will be the organisations capable of learning, adapting and reshaping themselves faster than the environments around them change. In other words, they will be Polymorphic.

And the leaders who guide them there will increasingly be Enterprise Leaders.

As we covered in the Polymorphic Organisation - Chronicle V - Who Leads? we see how much leadership isn’t just about individual capability, but one of the most persistent mistakes in organisation life is not treating leadership as a system property.

For decades we have tended to explain organisational success or failure through the actions of individual leaders. We celebrate visionary CEOs, charismatic founders and transformational executives. Equally, when organisations struggle, we often seek out weak leaders, poor managers or capability gaps as the primary explanation.

This perspective is understandable. Individuals are visible. Systems are not.

Yet systems science invites us to consider a different possibility.

• What if leadership is not simply something people possess?

• What if leadership is something organisations produce?

When we observe courageous leadership, collaborative leadership, innovative leadership or adaptive leadership, we often attribute those behaviours to the qualities of the individual. Sometimes that is entirely justified. Character, experience, judgement and capability matter enormously.

But they never operate in isolation. Leadership emerges within a context; the quality of information flow influences decision-making. The distribution of authority influences initiative; the speed and visibility of feedback influences learning and the level of psychological safety influences candour.

The clarity of purpose influences alignment, and the design of incentives influences behaviour. Within that, the structure of power influences whose voice gets heard and whose voice gets ignored.

Taken together, these conditions shape what forms of leadership become possible.

This is why the same individual can appear highly effective in one organisation and significantly less effective in another. The person has not fundamentally changed. The system around them has.

Deming understood this when he argued that the vast majority of performance problems originate within systems rather than individuals. Peter Senge explored similar territory through the concept of systems thinking, showing how behaviours emerge from structures that often remain invisible to those operating within them. Margaret Wheatley, Russell Ackoff and Donella Meadows all pointed towards the same underlying truth: outcomes emerge from interactions, not isolated actors.

Leadership is no exception.

In this sense, leadership behaves much like culture. Few serious organisational thinkers today would argue that culture is simply the aggregate personality of the leadership team. We increasingly recognise culture as an emergent property of structures, norms, incentives, behaviours and relationships.

Leadership deserves similar treatment.

When organisations consistently produce political behaviour, risk aversion, learned helplessness, excessive deference or command-and-control management, it is tempting to conclude that they simply have poor leaders.

Yet a more useful question may be: What conditions are producing those forms of leadership?

Likewise, when organisations display extraordinary levels of initiative, collaboration, accountability and innovation, we should resist the temptation to assume they have simply recruited exceptional people.

Instead, we might ask: What conditions are making those behaviours more likely?

The implications are significant.

If leadership is treated solely as an individual capability, the solution to organisational challenges becomes leadership development. More training. More coaching. More competency frameworks. More assessment.

These interventions have value, but they often operate downstream of the conditions creating the problem.

If leadership is understood as a system property, the questions change.

• How are decisions made here?

• How is authority distributed?

• What behaviours are rewarded?

• Where does information flow freely?

• Where does it become trapped?

• How safe is it to challenge assumptions?

• How visible is performance?

• How quickly can learning occur?

• How easy is it for expertise to influence outcomes?

These become leadership questions because they shape the environment from which leadership emerges.

This is one reason I believe the Enterprise Leader and the Polymorphic Organisation are becoming increasingly important. The task is no longer simply to develop stronger leaders. It is to design stronger conditions for leadership.

The most adaptive organisations of the future may not be those with the most talented executives. They may be those that have become exceptionally good at creating environments where leadership can emerge from anywhere, intelligence can flow across boundaries and adaptation becomes a natural consequence of the system itself.

In that world, leadership ceases to be something concentrated in a handful of individuals at the top of a hierarchy.

It becomes a property of the organisation.

Systems science suggests a different perspective; that leadership is often an emergent property of organisational conditions. The quality of information flow, the distribution of authority, the speed of feedback, the scale of trust and the level of perceived organisational support and psychological safety.

And more starkly perhaps, the visibility of performance and the clarity of purpose that drives performance with an aim and discernible impact.

Change these conditions and leadership changes with them. Industrial organisations were designed around the concentration of authority. And we’re very much still in that paradigm. Polymorphic organisations, though, are designed around the distribution of intelligence.

In a world where knowledge is dispersed, expertise changes rapidly and AI can augment capability almost instantly, the challenge is no longer commanding work.It is orchestrating intelligence.

Then there’s energy that is enhanced and utilised because of that orchestrated, symphonic intelligence.

The Enterprise Leader becomes the steward of organisational energy.

They recognise that capability without energy produces frustration.

• Strategy without energy produces inertia.

• Technology without energy produces resistance.

• Culture without energy produces performance theatre.

Their role is not simply to ensure people can perform. It is to ensure the organisation possesses sufficient collective energy to adapt.

The Enterprise CPO is also an Oscillation Steward.

In Chronicle XII, we deepened the understanding that Change Management is over and in its place if a form of adaptability that is framed around the expanding and consolidating flow of Organisational Oscillation.

One of the assumptions behind most transformation programmes is that organisations move from one stable state to another. Increasingly, I believe that assumption is wrong.

Organisations today exist in a state of oscillation.

• The legacy organisation still exists.

• The future organisation already exists.

And most leaders are attempting to manage one whilst creating the other, yet the challenge is not replacing one system with another; it is helping both coexist long enough for adaptation to occur.

This is where the Enterprise Leader becomes indispensable. They are uniquely positioned to understand the emotional, structural and capability tensions created when two organisational realities operate simultaneously.

So we may have reached the point where the marginal return on leadership development is declining - not because leadership development lacks value - but because organisations continue to invest in leaders whilst underinvesting in systems.

• We coach individuals through conditions they did not create.

• We develop resilience for environments that remain unhealthy.

• We improve leadership behaviours whilst preserving structures that reward the opposite.

The future challenge may not be “How do we develop better leaders?”

It may be: “How do we design organisations where poor leadership struggles to survive?”

The Proficiency Stack of the Polymorphic Organisation’s Enterprise Leader.

Not competencies. Not a capability framework. Proficient traits. Bundled into a stack that is added to, expunged and more constant of the now and next capabilities, skills and competencies needed. What that might look for an Enterprise Leader (CPO or otherwise) is:

1. They are systems literate - they see patterns, feedback loops, dependencies and unintended consequences before others do.

2. They think in capabilities rather than jobs - they focus on what the organisation can do rather than how it is currently structured.

3. They design for adaptability - stability matters, but adaptability becomes the higher-order capability.

4. They understand power - not politics in the pejorative sense, but the distribution of authority, information and influence.

5. They are organisational diagnosticians - they rarely accept surface-level explanations for organisational problems.

6. They cultivate horizontal accountability - they understand that future organisations cannot rely solely on hierarchical control.

7. They are architects of flow - flow of information, decisions, capability, learning and value.

8. They are polymorphic themselves - able to move between strategist, designer, coach, facilitator, futurist, operator and steward depending on context.

9. They see AI as a redesign challenge - not a technology challenge.

10. They optimise for enterprise prosperity - not HR success.

That final point is important because it connects beautifully to the Human Economic Manifesto work I pulled together in 2022 (see here).

The Enterprise Leader is not there solely to create a successful corporate function. They are there to create an organisation capable of generating human, social, intellectual, material, natural and financial value simultaneously.

That’s a much bigger ambition and a much stronger calling to answer.

So what can leaders of any function - especially HR - do right now?

1. Start diagnosing systems, not symptoms

The next time engagement falls, performance stalls, leaders struggle, collaboration breaks down or AI adoption falters, resist the urge to immediately launch an intervention.

Instead ask:

• What conditions are producing this outcome?

• What incentives are shaping behaviour?

• What structures are reinforcing it?

• What information is missing?

• What assumptions are no longer serving us?

Enterprise Leaders spend less time solving problems and more time understanding how problems are produced.

2. Shift from jobs to capabilities/proficiencies

Most organisations still plan around roles, departments and reporting lines.

Start asking different questions.

• What capabilities create value here?

• Which capabilities are emerging?

• Which are declining?

• Where is expertise trapped?

• How easily can capability move to where it is needed?

The future organisation is likely to be designed around capabilities rather than positions.

Understanding that shift now creates strategic advantage later.

3. Audit the flow of the organisation

One of the hidden responsibilities of the Enterprise Leader is stewardship of flow.

Look at:

• How decisions move.

• How information moves.

• How learning moves.

• How resources move.

• How talent moves.

Most organisations don’t suffer from a lack of capability.

They suffer from friction.

The question becomes:

“Where does value get stuck?”

4. Build systems literacy in the executive team

Most executive teams remain collections of functional experts.

Far fewer operate as enterprise stewards.

Introduce systems mapping.

Use causal loops.

Explore organisational network analysis.

Study complexity science.

Create space to examine interdependencies.

The future advantage may not come from knowing more than competitors.

It may come from understanding connections they cannot see.

5. Treat AI as a redesign challenge

Don’t begin with technology.

Begin with work.

Ask:

• What work creates value?

• What work creates friction?

• What work creates learning?

• What work should remain deeply human?

• What work can be augmented?

The organisations gaining the greatest advantage from AI are redesigning work itself, not simply deploying tools.

6. Develop leadership ecosystems rather than leadership programmes

Most organisations still invest heavily in individual leaders.

Far fewer invest in the conditions that allow leadership to emerge.

Focus on:

• information transparency

• decision clarity

• psychological safety

• distributed authority

• rapid feedback loops

• peer accountability

The future may belong less to organisations with exceptional leaders and more to organisations that make leadership easier to emerge.

7. Become comfortable with Organisational Oscillation

Stop assuming transformation means moving neatly from one state to another.

Learn to work with both. The legacy organisation and the future organisation will coexist for some time.

Enterprise Leaders help organisations hold that tension productively. Not by forcing premature change. Not by preserving outdated models.

But by creating enough stability for adaptation to occur.

8. Ask a different leadership question

For decades, the dominant question has been:

“How do we develop better leaders?”

The Polymorphic Organisation invites a different question:

“How do we create systems where leadership can emerge, intelligence can flow and adaptation becomes natural?”

That may prove to be the defining leadership challenge of the next decade.

The journey towards a Polymorphic Organisation does not begin with a restructure, a new technology platform or a revised competency framework.

It begins with a shift in perspective.

The moment leaders stop seeing the organisation as a collection of functions and start seeing it as a living system.

The moment they move from controlling parts to stewarding interactions.

The moment they realise that the future of leadership may not be about creating stronger leaders at all, but creating stronger conditions for leadership, learning and adaptability to emerge.

If that proves true, the rise of the Enterprise Leader will not simply represent the next evolution of management.

It may mark the beginning of the transition from the mechanical organisation to the Polymorphic enterprise.

Perhaps the most important insight is that the Enterprise Leader is emerging not because any individual function is ascending in importance, but because organisational adaptability itself is becoming a strategic capability.

The Enterprise CPO happens to be uniquely positioned at the intersection of capability, culture, leadership, technology and design, making them one of the most likely architects of the Polymorphic Organisation.

For over a century we have organised around hierarchy, function and control. The few decades will likely be organised around capability, adaptability and flow. If that plays out aws I believe it will, the most influential leaders will not be those who manage functions most effectively. They will be those who understand how entire systems evolve.

And that is why the Enterprise Leader - and most significantly the Enterprise CPO - will become part of one of the defining leadership shifts in centuries - moving us from the Mechanical to a Polymorphic age.

Not in the shallow “angel numbers on Instagram” sense. In the deeper sense that humans have always used numbers to create meaning around thresholds, transitions and time itself.

Thirty-three sits in strange territory. It is the age associated with transformation and sacrifice in Christian tradition. Dante’s Divine Comedy is structured around it.

In numerology, 33 is sometimes called the “master teacher” number - linked to compassion, responsibility, consciousness and service beyond the self.

But there’s another reason it fits this piece.

33 is the age at which many people first realise that time is not infinite.

Not intellectually. Somatically. You feel it.

You stop experiencing life as an endless horizon and begin experiencing it as allocation. And that’s exactly where this Chronicle wants to go.

Not productivity hacks, nor optimisation culture, and certainly not “five ways to reclaim your morning.” But the deeper phenomenon:

Why does modern life feel like it is accelerating beyond human scale?
Why do so many people — even successful, capable, privileged people — feel permanently late to their own existence?

And what would a Polymorphic Organisation do differently?

This needs rhythm. Reflection. Science. Philosophy. Sociology. Systems thinking. And practical liberation.

So here’s the piece.

Polymorphic Brewing: Chronicle 33

The Collapse of Time

There is something happening to time.

Not clocks.
Not calendars.
Not astronomy.

Human time.

The felt experience of living; and almost everyone I speak to senses it now.

Time feels compressed.
Fragmented.
Over-allocated.
Hyper-scheduled.
Perpetually consumed before we have even arrived inside it.

Whole weeks disappear in administrative fog; we optimise calendars while starving meaning; we “save time” with technology only to discover the saved time has immediately been recolonised by more work, more expectation, more communication, more obligation, more availability.

It feels harder to breathe inside modern life.

Harder to wander, to disappear into curiosity, to follow instinct and certainly harder to do something gloriously unnecessary.

The other day I saw a post from someone attending an event in the USA and my first thought was not excitement - but astonishment.

Ten years ago, that would have been me. I would have booked flights impulsively.
Thrown things into a bag and followed an idea across continents. Said yes before practicality had chance to intervene.

Now?

I look at my calendar like an air traffic controller managing an overwhelmed runway system.

Client work.
Projects.
Writing.
Thinking.
Relationships.
Family.
Admin.
Travel.
Preparation.
Recovery.
Life maintenance.

Every day feels like a negotiation between competing urgencies. And I know I’m not alone. People everywhere are quietly asking the same question:

What happened to time?

The Great Compression

There is actual science behind this and several streams of research now point toward what sociologists and psychologists describe as temporal compression.

Put simply, human beings are experiencing more cognitive, emotional and informational events per unit of time than at any point in history.

The brain does not experience time objectively. It experiences density, and modern life is extraordinarily dense.

Emails.
Notifications.
Meetings.
Context switching.
Platform hopping.
Infinite media.
Infinite comparison.
Infinite updates.
Infinite access.

Even rest has become informational.

We no longer merely sit quietly. We consume while recovering.

Music.
Podcasts.
Videos.
News.
Threads.
Messages.
Content.

The mind rarely empties now.

And when the brain cannot consolidate experience properly, time begins to feel faster.

There’s compelling neuroscience behind this.

Memory formation plays a huge role in our perception of time. Novelty-rich experiences create deeper encoding in the hippocampus, making periods of life feel expansive in retrospect. Repetition and administrative sameness do the opposite.

This is why childhood summers felt endless. Everything was new.

Now? Many adults experience weeks composed largely of operational repetition.

• The brain stops richly encoding.

• Life becomes cognitively flattened.

• And time appears to accelerate.

But there’s another layer too.

The sociologist Hartmut Rosa calls this social acceleration.

Technology was supposed to create leisure. Instead, every technological gain increased expectations.

• Email sped communication up — so now we expect rapid replies.

• Remote work created flexibility — so now availability became permanent.

• AI increases productivity — so organisations increase output expectations.

Every efficiency gain becomes absorbed into the system.

We do not gain time - we intensify activity.

This is one of the great illusions of modernity.

We solved for speed but not for sufficiency.

The Tyranny of Infinite Accessibility

There used to be natural boundaries around human existence.

• The office closed.

• Shops shut.

• Letters took days.

• People disappeared for weekends.

• Travelling meant genuine absence.

Now we exist inside perpetual partial presence: Always reachable, potentially responsive, always slightly “on.”

And this matters psychologically far more than many organisations realise. Because humans are not merely exhausted by work volume.

We are exhausted by anticipatory cognition.

The constant low-level awareness that something may require us at any moment. This creates what neuroscientists sometimes call continuous partial attention. You never fully arrive anywhere.

Not in work. Not in rest. Not even in relationships.

Part of the mind remains scanning. And when the nervous system cannot fully complete cycles of attention and restoration, time itself begins to feel hostile.

This is why people increasingly describe modern life with phrases like:

“I’m drowning.”
“I can’t catch up.”
“I’m behind.”
“I never stop.”
“I don’t know where the year went.”

These are not merely metaphors.

They are symptoms of systemic temporal overload.

The Hidden Economics of Time Poverty

What fascinates me is that time poverty increasingly affects even people with relative privilege. Historically, we associated time scarcity with material hardship alone. But now highly educated professionals, leaders, consultants, creatives and knowledge workers often feel profoundly time-poor despite technological abundance.

Why?

Because modern economies increasingly monetise attention itself. Not simply labour.

Attention.

And attention is temporal.

• Every platform competes to occupy human consciousness.

• Every organisation seeks responsiveness.

• Every system seeks engagement

• Every algorithm seeks retention.

The result?

Humans increasingly experience themselves not as living beings, but as throughput systems. We become processors and administrators of escalating informational flow.

And something deeply human starts disappearing.

Wonder.
Presence.
Serendipity.
Drift.
Contemplation.
Silence.

Even boredom has nearly vanished from modern civilisation. But boredom was once a gateway state.

It created imagination.
Reflection.
Creativity.
Spaciousness.

Now we anaesthetise every empty moment.

And the cost is enormous.

Butterfly Fields

More recently, I wrote about “Butterfly Fields” (Chronicle XXXII in fact).

It barely touched the algorithm, which is ironic really. Because it may have been one of the most important things I’ve written.

The Butterfly Field is the opposite of optimisation culture.

It is the idea that human flourishing requires unstructured ecological spaces where emergence can occur. Butterflies do not appear in concrete efficiency corridors; they appear in living fields.

Wildness, variation, pollination, movement and light. Human beings need psychological Butterfly Fields too.

Places where not every minute is monetised.
Where not every action is instrumental.
Where thought can wander.
Where conversations meander.
Where curiosity is allowed to lead without immediate utility.

Many organisations have systematically destroyed these spaces in pursuit of measurable efficiency. And then they wonder why creativity collapses, innovation stalls and engagement declines.

Why everyone feels permanently depleted despite productivity software, workflow systems and AI augmentation is because humans are not machines that improve infinitely through compression.

Past a certain point, compression destroys vitality.

The Organisational Lie

Most organisations still operate on an industrial assumption: That more output squeezed into less time equals progress. But this increasingly collides with biological reality - humans are rhythmic creatures and not linear ones.

We oscillate.

We need cycles: Expansion and contraction; intensity and recovery; focus and diffusion; performance and reflection.

The industrial era distrusted rhythm because machines do not need restoration. Polymorphic Organisations see that recovering rhythm as strategic infrastructure.

Not wellness theatre, not mindfulness webinars, not resilience training designed to help people survive unsustainable systems.

Actual structural redesign.

Many organisations are not suffering from poor time management. They are suffering from temporal architecture failure. The system itself produces fragmentation.

And no amount of colour-coded calendars can solve structurally incoherent work.

Why “Time Management” Fails

Most time management advice fails because it treats humans like logistical problems.

Prioritise.
Optimise.
Batch.
Automate.
Delegate.

Some of this helps temporarily, but it rarely addresses existential overload. Because the deeper issue is not lack of scheduling skill; it is loss of sovereignty over attention.

People no longer feel ownership over their own cognitive landscape. And once that happens, life begins feeling externally authored. This is why even highly productive people increasingly feel strangely detached from their own existence.

They are moving constantly but rarely inhabiting their movement. The calendar becomes reality. And eventually people stop asking:

“What matters?”

They simply ask:

“What’s next?”

That is a dangerous transition.

Because “what’s next?” is infinite. There is always another thing.

Polymorphic Time

A Polymorphic Organisation would approach time differently. Not as a uniform commodity but as a living ecology.

Different work requires different temporal states.

• Deep thinking cannot exist inside perpetual interruption.

• Creativity requires spaciousness.

• Learning requires reflection.

• Relationships require presence.

• Strategy requires cognitive altitude.

Yet most organisations force all forms of work into the same temporal container.

• Meeting-heavy fragmentation.

• Constant responsiveness.

• Administrative overload.

• Artificial urgency.

Polymorphic design asks a different question: “What temporal conditions allow humans to thrive and contribute meaningfully?”

That changes everything, because suddenly the objective is not squeezing more activity into the day: It is designing healthier temporal ecosystems.

And that leads to practical shifts. Real ones.

Not productivity cosplay.

Things That Actually Bend Time Back Toward Us

Not management - Recovery.

Not optimisation - Rehumanisation.

Here are some things I increasingly believe matter.

1. Protect Cognitive Monoculture Zones

Most people never fully enter deep thought anymore. Their cognition is shattered into fragments.

A Polymorphic Organisation should create sacred, uninterrupted zones for meaningful work.

No meetings.
No Slack.
No notifications.
No response expectations.

Just immersion.

One hour of uninterrupted deep cognition often produces more meaningful output than six hours of fractured attention.

2. Restore Temporal Diversity

Not every day should look the same. Humans need different temporal textures.

Some days expansive.
Some collaborative.
Some reflective.
Some exploratory.

Industrial work standardised time.

Polymorphic work diversifies it.

3. Stop Treating Availability as Commitment

Constant accessibility is not dedication.

Often it is anxiety.

Or performative responsiveness.

Or survival behaviour inside overloaded systems.

Healthy organisations should reward clarity and contribution - not digital hyper-presence.

4. Reintroduce Drift

Drift matters.

Walking without purpose.
Reading without extraction.
Conversations without agenda.
Thinking without deliverable.

Many breakthroughs emerge from non-linear cognitive wandering. The problem is modern systems classify all non-instrumental time as inefficiency.

But that “inefficiency” is often where humanity lives.

5. Design Organisational Breathing Spaces

Nature oscillates.

So should organisations.

Not every quarter should feel like emergency mobilisation.

There should be intentional cycles of consolidation, reflection and recovery.

This connects directly to Organisational Oscillation (see Chronicle XII here)

Constant acceleration eventually becomes organisational hypoxia.

6. Reduce Administrative Gravity

Many people are not overwhelmed by meaningful work.

They are overwhelmed by coordination overhead.

Approvals.
Status updates.
Duplicated systems.
Meetings about meetings.
Workflow administration.

Organisations often mistake administrative activity for operational sophistication.

Usually it is just drag.

7. Recover Presence Rituals

One of the reasons older social structures felt slower was ritual.

Meals.
Conversations.
Communal pauses.
Seasonal rhythms.

Modern work culture atomised many of these.

Polymorphic cultures should intentionally restore collective moments of presence.

Not forced fun. Human anchoring.

The Real Scarcity

I don’t actually think time is the scarcest resource anymore.

Attention is.

And beneath attention sits something even more precious:

Aliveness.

That feeling of actually inhabiting your own life while it is happening. Not merely administrating it. And maybe that is why so many people feel emotionally exhausted despite achieving so much. Achievement without temporal spaciousness becomes strangely hollow.

You arrive at the thing only to discover you were never really there for the journey toward it.

Chronicle 33

Maybe that’s why this Chronicle needed to be number 33. Because this feels like a threshold conversation; Not about productivity. About civilisation.

About the growing mismatch between biological humans and accelerationist systems. And about the possibility that organisations must now evolve not simply economically - but temporally.

And perhaps the future belongs not to the fastest organisations; but to the ones capable of restoring humane rhythms inside complexity.

The ones brave enough to create Butterfly Fields again.

Places where people can breathe.
Think.
Wander.
Notice.
Recover.
Imagine.

Places where time stops feeling like an adversary.

And starts becoming inhabitable again.

Because maybe the deepest innovation of the next decade will not be artificial intelligence.

It will be the rediscovery of human tempo.

Bringing this one into land.

Chronicle 33 isn’t just another episode. It it perhaps where the real work begins. Not with another productivity framework. Not with squeezing more output from exhausted humans.

But with a collective act of courage:
to redesign the relationship between people, work, rhythm and meaning itself.

Because the temporal crisis we are living through is not simply operational. It is philosophical.

We have built systems that treat human beings as infinitely elastic — endlessly reachable, endlessly adaptable, endlessly productive — and then we act surprised when anxiety, burnout, emotional numbness and disconnection become endemic.

A Polymorphic Organisation cannot merely be structurally different.

• It must become temporally different.

• It must reject the industrial fantasy that all value emerges from acceleration.

• And instead recognise something older, wiser and more human:

That flourishing requires cadence.

Pulse. Breathing room. Alternation.

The future of healthy organisations may depend less on how fast they move and more on whether they can restore humane temporal conditions inside complexity.

That means designing systems where people are not permanently cognitively occupied.

I love it when I’m inspired by others’ work. It proves what the great Don Tapscott once said "We’re not in an information age. We’re in an age of networked intelligence."

How often I’ve quoted this I don’t know. It became so central to my thinking in the previous “peak future of work” era - the 2010s.

So when I read this morning Mike Walsh’s recent piece (here) - The Rise of the High Throughput Operator - it quietly reframed and named everything I’ve been thinking about this past 2 months or so.

What I thought was work intensity kind of is, but not quite.

What I thought were irreconcilable tensions in how work is, kind of is, but not totally.

What I thought were patterns I couldn’t comprehend in work, kind of where, but not exactly that.

It was the framing of work decomposition; the creation of intelligence, the deployment of systems and machines, and the channelling of self to be a High Throughput Operator.

It’s wasn’t even the provocative talk of tokens, or even the challenging idea that underutilisation of AI is the new inefficiency.

It’s something subtler.

The shift from asking:

“Am I doing enough?”

to asking:

“Am I directing enough intelligence?”

That’s the hinge for me in all of this.

And once you see it, it becomes difficult to unsee. Because it exposes something deeper than a productivity shift. It reveals a structural change in how work itself comes into being.

The Work That Isn’t There Yet

For most of our working lives, we’ve operated under a comforting assumption:

That the work exists and that it is, definable, decomposable and schedulable.

Even in Agile environments, where we embrace iteration and uncertainty, we still assume that the work can be broken down into:

• stories

• tasks

• increments

But increasingly, that assumption is breaking down. We are encountering work that is not yet fully formed.

Work that arrives as:

• fragments

• tensions

• half-thoughts

• emerging patterns

Work that cannot yet be cleanly decomposed; because it hasn’t stabilised into something decomposable. And yet, our instinct is still to push it into structure too early.

The Violence of Premature Structure

There is a quiet “thrashing” in how organisations treat emerging work as we rush to:

• define

• categorise

• prioritise

• execute

We ask:

• “What’s the deliverable?”

• “What are the tasks?”

• “Who owns this?”

But in doing so, we often collapse possibility too soon. We turn exploration into obligation; curiosity into commitment; signals into tasks.

And something gets lost. Not just nuance, but potential.

A Different Kind of Worker Is Emerging

Walsh calls them “high throughput operators” And he’s right to notice the shift.

We are seeing people who:

• run multiple AI agents in parallel

• orchestrate flows of output

• produce at speeds previously unimaginable

But the language of “throughput” doesn’t quite capture what’s happening. Because this isn’t about volume alone. It’s about composition.

What we’re really seeing is the emergence of what I am calling:

Cognitive Orchestrators

People who don’t just do the work, they design how work gets done.

They are showing an adeptness to frame problems, direct intelligence and shape outputs across systems. And crucially, they operate in environments where intelligence is no longer scarce.

When Intelligence Becomes Abundant

This is the real shift. For decades, the constraint in knowledge work was human cognition. Now we have AI, that expands thinking capacity. Analysis becomes cheaper, and generation becomes instantaneous. Which means the bottleneck moves.

Not to effort. Not to output. But to something far more subtle:

The ability to discern what matters - and to direct intelligence toward it

And that’s where things get much more interesting. Because before we can direct intelligence, We have to know what we are directing it at.

The Missing Stage

This is where my own work - and a recent experiment I’ve been running - comes into play. In the rush toward execution, something has been missing.

A stage that sits before:

• backlog creation

• task definition

• sprint planning

A stage that is neither:

• ideation

• nor planning

• nor decision-making

But something else entirely.

I’ve started calling it:

Catching Butterflies

Not Capturing. Not Pinning. Catching.

The metaphor matters. This isn’t about capturing ideas and pinning them down - so they become lifeless, categorised, fixed.

It’s about:

• noticing them

• holding them lightly

• allowing them to move

• creating a space where they can exist without being forced into shape

Butterflies are fragile. They don’t survive heavy handling - and neither do early-stage ideas in complex environments. So instead of forcing them into structure, we create a habitat.

A place where:

• signals can gather

• patterns can emerge

• connections can form

Before we decide what any of it means.

A Pre-Kanban World

In practical terms, what I’ve been experimenting with is a kind of:

Pre-Kanban system

Not a backlog. Not a task board. But a sense-making field. A place where things land in their raw form:

• ideas

• questions

• challenges

• fragments

• research

• conversations

Not yet shaped nor yet prioritised, and not yet turned into work.

And importantly: Not judged too early.

From Butterflies to Work

Only after this stage do we begin to move toward structure. And the movement there is somewhat different. Because it’s not immediate decomposition into tasks, it’s more a gradual, thoughtful shift into shaping.

Something like:

• Signals begin to cluster

• Themes start to emerge

• Tensions become clearer

• Patterns reveal themselves

And then, only then, do we begin to ask:

What is the work here?

Not:

What are the tasks?

But:

What is actually trying to happen?

Work Decomposition Reimagined

This reframes decomposition entirely, because instead of breaking down predefined work, we are decomposing emerging understanding. And that’s a very different act.

It requires:

• patience

• pattern recognition

• judgment

• restraint

It aligns not just with Agile, but with deeper scientific traditions:

• Herbert Simon’s work on problem structuring

• Karl Weick’s sensemaking

• Cynefin’s inviting sense-making and “where we are” and this movement from complexity to an early form of clarity

• Cognitive science on pattern formation before categorisation

In each case, the sequence matters. And we’ve been getting it slightly wrong.

What This Means for Organisations

This isn’t just about individuals becoming better at using AI, it’s about organisations needing to evolve how they create work. In Polymorphic Organisations, this becomes critical. Because:

• work is fluid

• roles are dynamic

• structure is adaptive

You cannot rely on fixed pipelines of predefined work. Instead, you need:

systems that allow work to emerge intelligently

Catching Butterflies as an Operating Layer

In that sense, “Catching Butterflies” becomes:

An operating layer in the Polymorphic Organisation

Not a tool, nor a process, but a capability. A way of holding ambiguity; sensing signals; and allowing meaning to form

Before committing to action.

From Orchestrators to Ecosystems

The “cognitive orchestrator” is an important step, but it’s still individual-centric. The real shift is systemic. From individuals directing intelligence; to organisations behaving like intelligence ecosystems. Very reminiscent of Jon Husband’s Wirearchy concept.

Where:

• ideas flow

• signals interact

• work emerges dynamically

• execution adapts continuously

What You Can Do Now

This is not theoretical, in fact you can begin this tomorrow. Not by necessarily redesigning your entire organisation, but by introducing a new habit. A new space. A new question.

1. Create a Butterfly Field

Set up a simple space (digital or physical) where:

• nothing has to be actionable

• nothing has to be owned

• nothing has to be prioritised

Just captured - lightly - and without pressure.

2. Resist Immediate Structuring

When something lands, don’t ask “What’s the task?”

Ask instead:

• “What might this connect to?”

• “What is this pointing at?”

Let it breathe for a bit. And let you be more contemplative, thoughtful, immersed, distant even. But don’t rush in. Be more slow, deliberate, spacious even (HT Megan Reitz)

3. Sense Before You Shape

Regularly step back and look at the field, not for tasks, but for patterns; clusters; tensions and themes. This is where work begins to form.

4. Then — and Only Then — Decompose

Once something stabilises:

• define it

• shape it

• break it down

• commit to it

Now it’s ready. Because now it’s real.

The Deeper Shift

If you step back, this all points to something bigger. We are moving from a world where work is given, to a world where work is constructed - continuously. Collectively and more intelligently.

Final Reflection

Mike Walsh is right; underutilisation of intelligence is becoming a real risk. But it’s not just about using more AI. It’s about using it well. And that begins not with execution, but with discernment.

Closing Line

In a world where intelligence is abundant, the rarest skill is not doing the work, but seeing what the work needs to become.

This is about ending. From a different perspective. A Polymorphic one. Where ends are merely new beginnings but absolutely necessary.

Markets shift, so must Organisations

E = TC²

Stephen R Covey gave the world a powerful principle with “Begin with the end in mind.” It works beautifully in a world where outcomes can be defined, planned, and achieved.

But this Chronicle - and the whole Polymorphic Organisational thesis - sits in a different world.

A world where:

• There is no singular fixed “end”

• Markets don’t stabilise long enough to aim at one

• Organisations must continuously reconfigure, not arrive

So the idea of “the end” starts to feel less relevant and outdated.

Only a series of ends.

Each one a temporary coherence before the system reshapes itself again.

We too often talk about “the end” as though it is something fixed.

But perhaps an end is something else entirely. A new equation for the end (in an organisational, enterprise and work sense of course) is perhaps:

E = TC²

End = Temporary Coherence <Squared>

A moment where temporary coherence intensifies - where things align just enough, long enough, to give the impression of completion.

But only for a moment.

Because what we call an end, is simply the system pausing in coherence before it begins again.

E - End

Not a destination.
Not a finish line.
But a moment where things come together.

TC - Temporary Coherence

A state where:

• Effort aligns

• Form stabilises

• Meaning holds (briefly)

• The system “makes sense” - for now

But only for now.

Squared (²) - Amplification

Because:

• Coherence isn’t linear

• It compounds

• It intensifies

• It creates a felt sense of completion

Even though it’s temporary.

The Full Expression

An “End” is a moment where temporary coherence intensifies to the point that it feels complete.

But it isn’t.

Confused? Read on…

Chronicle 31 therefore is: The Market is Speaking - But Are You Designed to Hear It?

Markets do not collapse quietly.

They don’t send formal notices, or neatly packaged signals, or politely timed warnings that align with quarterly cycles. They move in pulses. In fragments. In contradictions. In sudden accelerations and quiet withdrawals.

• They whisper.

• They surge

• They disappear.

And yet, most organisations behave as though demand is something stable. Something measurable. Something that, once understood, can be forecast, planned, and optimised against.

It’s a comforting fiction. But a fiction nonetheless. Because demand is not a dataset.

It is a living system.

The First Misunderstanding: Demand is Not Data

Somewhere along the line, we replaced sensing with reporting.

1. Dashboards became proxies for reality.

2. Customer surveys became stand-ins for behaviour.

3. Forecasts became substitutes for uncertainty.

And in doing so, we created a dangerous illusion: that the market can be known in advance.

Classical economic models reinforced this belief. Rational actors. Perfect information. Equilibrium states. A world in which supply and demand meet cleanly, predictably, almost elegantly.

But real markets do not behave like this.

The work of Daniel Kahneman fundamentally disrupted this assumption. Human decision-making, he showed, is not rational but bounded - shaped by bias, heuristics, emotion, and context. People do not act as stable agents of logic; they respond as fluctuating beings within shifting environments.

Layer onto this the insights of Nassim Nicholas Taleb - that the most consequential events are often the least predictable - and the illusion begins to fracture completely.

Markets are not just complex.
They are non-linear. (Per the BANI acronym of course)

Small signals can trigger massive shifts. Long periods of stability can precede sudden rupture. What appears predictable; often isn’t.

So the idea that demand can be fully captured through historical data and projected forward is, at best, incomplete — and at worst, deeply misleading.

Demand is not something to predict.

It is something to sense, interpret, and respond to — in motion.

Why Organisations Still Get It Wrong

If the evidence is so clear, why do so many organisations continue to operate as though demand is stable?

Because their design depends on it.

Modern organisational structures - particularly those shaped during the industrial and post-industrial eras - are pyramidally-optimised for:

• Efficiency

• Repeatability

• Control

• Scale

Not for fluidity; not for emergence; not for continuous reinterpretation.

And so, three patterns emerge - again and again.

1. The Illusion of Knowing

“We understand our market.”

It’s a familiar refrain. Often backed by years — sometimes decades — of success. Deep expertise. Category leadership. Brand recognition.

And therein lies the trap.

Success creates coherence.
Coherence creates confidence.
Confidence, over time, becomes certainty.

But markets do not reward certainty. They seem to punish it.

Organisations begin to see what they expect to see. Signals that confirm existing models are amplified. Signals that challenge them are ignored, dismissed, or explained away.

This is not failure of intelligence.
It is failure of perception.

2. Structural Lag

Even when signals are recognised, the response is often too slow.

Why?

Because the organisation itself cannot move at the speed of the market.

Decision-making layers dilute urgency.
Approval processes introduce delay.
Functional silos fragment understanding.

By the time insight travels from the edge of the organisation to the centre - and back again, in the form of action - the market has already moved on.

The system is not broken.

It is simply too slow for the environment it inhabits.

3. Identity Rigidity

“This is who we are.”

There is power in identity. It anchors purpose, aligns effort, and builds trust.

But it can also constrain adaptation.

When identity becomes too fixed - when organisations define themselves too narrowly by product, category, or legacy - they lose the ability to evolve with shifting demand.

They become attached to what they have been, rather than open to what they might become.

History offers countless examples (yes, Kodak, Blockbuster, Nokia are overused but also):

• Pan Am

• Thomas Cook

• Carillion

• Debenhams

• Sears

• Toys R Us

• Blackberry

• MySpace

• Palm

• BHS

• MFI

• Saab

These were not failures of intelligence or innovation. They were failures of alignment between organisational form and market reality.

Markets didn’t kill these companies.

Misalignment did.

The Nature of the Market: A Complex Adaptive System

To move forward, we need a different lens.

Markets are not machines.

They are complex adaptive systems.

This perspective, drawn from fields such as complexity science and systems theory, reframes how we understand demand.

In complex systems:

• Agents interact dynamically (customers, competitors, partners)

• Patterns emerge from interactions, not central control

• Outcomes are unpredictable, but not random

• Feedback loops shape future behaviour

The Cynefin Framework, developed by Dave Snowden, offers a useful distinction here:

• Complicated domains - where cause and effect can be analysed

• Complex domains - where cause and effect can only be understood in retrospect

• Chaotic domains - where who knows what caused it and where it’s going

Markets sit firmly in the complex domain.

Which means:

You cannot analyse your way to certainty.
You cannot plan your way to stability.

You must probe, sense, and respond.

This is not a philosophical stance.

It is a structural requirement.

From Insight to Action: The Gap Most Organisations Cannot Bridge

Many organisations, to their credit, have invested heavily in understanding their markets.

• Customer analytics teams.

• Market research functions.

• Data science capabilities.

The problem is not a lack of insight.

It is a lack of responsiveness.

There is a gap - often vast - between what the organisation knows and what it is able to do.

1. Signals are captured.

2. Reports are generated.

3. Presentations are shared.

And then… very little changes.

Because the organisational system itself is not designed to translate insight into action at speed. It is designed to stabilise, to optimise, and to protect.

Not to adapt continuously.

So even when the market is “heard”; the organisation cannot respond in time for it to matter.

A Different Approach: Real-Time Sensing from the Edge

What if we inverted the model?

Instead of centralising insight and distributing action…
What if sensing and responding were co-located?

At the edges of the organisation.

Where interaction with the market actually happens.

This is not a new idea - but it is one that has rarely been fully realised.

It draws on several strands of theory and practice:

• Distributed cognition - intelligence emerging across networks, not central nodes

• Lean thinking - shortening feedback loops between action and learning

• Agile and product thinking - iterative, responsive development cycles

• Complex adaptive systems - local agents responding to local conditions

In this model:

• Teams closest to customers sense changes in demand directly

• They have the autonomy to interpret those signals

• And the authority to respond — rapidly, iteratively, experimentally

The organisation becomes less like a hierarchy and more like a living network of sensing-response units.

See Haier, Handelsbanken, Spotify and others.

Enter the Polymorphic Organisation

This is where Polymorphism comes into its own.

Because the challenge is not just about sensing.

It is about becoming capable of multiple responses - simultaneously.

Polymorphism, at its core, is the capacity to take on different forms depending on context.

In organisational terms, this means:

• Not one operating model - but many (nested, adjacent, underpinning, temporary and emergent)

• Not one way of working - but a repertoire (think Broadway or the West End - acting in many different productions)

• Not one response to demand - but a portfolio of responses (think Streaming Services that are data and demand-led and introduce new products and service propositions to retain viewers)

It is the difference between adaptation and adaptability.

Four Capabilities of a Polymorphic Response System

Let’s bring this to life.

A Polymorphic Organisation, designed for shifting market demand, exhibits four critical capabilities.

1. Distributed Sensing

Markets are not read from dashboards.

They are read through interaction.

This means:

• Frontline teams are not just delivery units — they are intelligence nodes

• Customer conversations are treated as data streams

• Partners and ecosystems become extensions of sensing capability

Information flows horizontally, not just vertically.

The organisation listens everywhere.

2. Adaptive Form

Structure is not fixed.

It shifts in response to demand patterns.

Teams form, dissolve, and reconfigure based on:

• Emerging opportunities

• Changing priorities

• Real-time feedback

This reflects principles seen in network theory and even biological systems — where form follows function, dynamically.

The organisation becomes structurally and fluently fluid.

3. Portfolio Thinking (Beyond the Product)

Demand is not singular.

It is fragmented, evolving, and often contradictory.

So rather than betting on one product, one strategy, one path — Polymorphic Organisations operate through portfolios:

• Multiple experiments running in parallel

• Micro-offers tailored to different segments

• Continuous evaluation — scaling what works, letting go of what doesn’t

This aligns with evolutionary principles:

Variation. Selection. Retention.

Not as theory - but as operational logic.

4. Temporal Agility

Speed alone is not enough.

What matters is timing.

When to act quickly.
When to stabilise.
When to explore.
When to exploit.

This is where the concept of Organisational Oscillation fits powerfully:

• Expansion phases - experimentation, movement, divergence

• Consolidation phases - integration, coherence, focus

The organisation moves in rhythm with the market - not against it.

Volatility, Shock, and the Case for Anti-Fragility

We cannot talk about markets without acknowledging shock.

Disruption. Crisis. Black Swan events.

The work of The Black Swan and Antifragile highlights a crucial distinction:

• Fragile systems break under stress

• Robust systems resist stress

• Anti-fragile systems benefit from stress

Most organisations aim for robustness: Stability. Resilience. Continuity.

But in volatile environments, robustness is not enough.

Because the nature of the shock may be entirely outside what has been planned for.

Polymorphic Organisations take a different stance.

They do not try to eliminate volatility.

They expose themselves to it - intelligently.

Through:

• Distributed experiments

• Decentralised decision-making

• Rapid feedback loops

Failure is localised.
Learning is amplified.

And over time, the system becomes stronger because of variability, not in spite of it.

A Necessary Tension: Serving vs Shaping Demand

At this point, a caution is needed. Because responsiveness, taken too far, becomes reactivity: Chasing every signal; Following every trend; Optimising for short-term demand at the expense of long-term value.

Markets are not neutral.

They can generate demand that is:

• Extractive

• Unsustainable

• Misaligned with human or societal well-being

So the question cannot simply be:

“How do we respond to demand?”

It must also be:

“What kind of demand are we choosing to serve — and amplify?”

This is where purpose, ethics, and design intersect.

Polymorphic Organisations are not just responsive systems. They are intentional systems.

Capable not only of adapting to markets; but of shaping them.

The Deeper Truth: This is a Design Problem

What becomes clear, across all of this, is that market responsiveness is not primarily a strategy issue.

It is a design issue.

You can have:

• The best data

• The clearest insights

• The most talented people

And still fail to respond effectively.

If your organisational form cannot translate sensing into action, your structures slow down response, your identity constrains adaptation.

Then no amount of strategy will compensate.

Because the system itself is misaligned with the environment it operates in.

Let’s get real

You are probably wondering:

How do enterprises of varying sizes do this now? Surely they can’t wait for their Polymorphic (or if they’d rather their annual “transformation programme”) to complete?

Now is the time to start.

And no Polymorphic state is ever complete, only an end into a new beginning. Constantly.

Anyway, for the pragmatists amongst us, here’s how you can do this NOW. And end your market myopia and become more adept at micro and macro vision into action.

Enterprise Market Listening Into Action

SMEs: The Advantage of Proximity (Use It or Lose It)

Small and medium-sized enterprises already have something most large organisations are desperately trying to recreate:

Closeness to the market.

1. Less hierarchy.

2. Shorter feedback loops.

3. Direct customer contact.

But here’s an uncomfortable reality:

Many SMEs behave like scaled-down corporates rather than amplified sensing systems.

What to Do Now

1. Turn Every Customer Interaction into Intelligence

Not just sales. Not just service.

Every interaction becomes a signal:

• What are customers really asking for?

• What are they struggling to articulate?

• Where are they improvising around your offering?

Action:
Create a simple weekly ritual:

• 30-minute “Market Signals” huddle

• Everyone brings 1 observation from the front line

• No slides. No over-analysis. Just raw sensing

This builds collective perception.

2. Run Micro-Experiments Relentlessly

SMEs often wait too long to “get it right.” But markets reward movement, not perfection.

Action:
Adopt a simple rule:

• Every month » 2–3 small experiments

• New offer, tweak, pricing shift, channel test

• Measure lightly, learn quickly

This aligns with Lean Startup thinking (Eric Ries), but more importantly, it builds muscle for responsiveness.

3. Loosen Role Boundaries

Rigid roles kill responsiveness. In SMEs, this is often cultural rather than structural.

Action:
Introduce “fluid contribution”:

• Who can help solve this > regardless of role?

• Who has proximity to the issue?

You don’t need a new org design. Just permission.

SME Summary

You don’t need Polymorphism as a model. You need to stop suppressing the polymorphism you already have.

Larger Organisations — Breaking the Structural Lag

This is where it gets harder. Because the challenge is not awareness.

It’s inertia.

You have:

• Data

• Insight

• Capability

But the system cannot move.

What to Do Now

1. Create Edge Teams with Real Authority

Not innovation labs. Not sandbox teams.

Actual market-facing units with decision rights.

Action:

• Identify 2–3 key customer segments

• Create cross-functional teams around them

• Give them authority to adapt offer, pricing, experience

This draws on research like Amy Edmondson - autonomy + safety drives learning and performance.

2. Shorten the Distance Between Signal and Decision

Map how long it takes for:

Customer insight » Decision » Action

You may not like what you find.

Action:

• Identify 3 biggest delays

• Remove one layer of approval

• Push decisions closer to the edge

Even a 20% reduction in decision latency changes responsiveness dramatically.

3. Shift from Projects to Products (or Value Streams)

Projects assume:

• Defined scope

• Predictable outcomes

Markets don’t behave like that.

Action:
Reframe key work as:

• Ongoing value streams

• Continuous iteration

• Persistent ownership

This aligns with Agile and product models - but more importantly, it aligns with ongoing demand sensing.

4. Build a Portfolio, Not a Bet

Most large organisations still operate on:

• Big bets

• Long cycles

• High commitment

Which is fragile.

Action:

• Allocate 10–15% capacity to experimentation

• Run parallel initiatives

• Actively kill underperforming ones

This is where Taleb’s logic of optionality becomes practical.

Large Organisation Summary

You don’t need to redesign everything.

You need to create pockets where the future can operate differently - now.

Global Giants — From Control to Capability

For global organisations, the issue is even deeper.

It’s not just structure.

It’s philosophy.

Control has been the dominant logic:

• Standardisation

• Consistency

• Efficiency at scale

But markets are fragmenting faster than global models can adapt.

What to Do Now

1. Move from Centralised Insight to Networked Sensing

Global firms often centralise intelligence:

• Strategy teams

• Global marketing

• Data hubs

But this creates distance from reality.

Action:

• Build regional sensing nodes

• Connect them horizontally (not just to HQ)

• Share patterns, not just reports

This reflects principles of network science and distributed intelligence.

2. Allow Local Variation (Within Strategic Guardrails)

Standardisation is efficient.

But it kills responsiveness.

Action:
Define:

• What must be consistent (purpose, brand essence)

• What can vary (offer, pricing, experience)

Then actively encourage variation.

This is Polymorphism in practice — same identity, different expression.

3. Invest in Dynamic Resource Allocation

Annual budgets are too slow.

Markets don’t wait.

Action:

• Introduce quarterly or rolling funding

• Redirect resources based on emerging demand

• Reward reallocation, not just execution

This aligns with modern capital allocation research and adaptive strategy models.

4. Embrace Organisational Oscillation

Global firms often over-index on stability.

But The Polymorphic princple of oscillation is critical here.

Action:
Design for:

• Expansion phases → exploration, experimentation

• Consolidation phases → scaling, integration

Make this rhythm explicit.

Not accidental.

Global Summary

You don’t need to abandon scale.

You need to make scale adaptive.

Across All Three: Five Universal Moves

Regardless of size, five actions cut across everything:

1. Get Closer to the Market

Not through reports - through contact.

2. Shorten Feedback Loops

Speed of learning > perfection of planning.

3. Decentralise Response

Push action to where the signal is.

4. Increase Optionality

More small bets > fewer big bets.

5. Redesign for Flow, Not Control

Work should move with demand, not against it.

A Final Challenge

Here’s the uncomfortable but necessary truth:

Most organisations do not fail to respond to market demand because they lack insight.

They fail because:

• It is inconvenient to change

• It disrupts power structures

• It exposes uncertainty

• It challenges identity

So they delay. They rationalise. They optimise what already exists.

Until the market moves beyond them.

Pre-Closing Reflection

So perhaps Chronicle 31 doesn’t end with Polymorphism as the destination.

But as a question:

How much of your organisation is currently capable of sensing and responding to real market demand — in real time?

• 6%?

• 12%?

• 25%?

And more importantly:

What would it take to move just one step further along that curve?

Because the future won’t be won by those who transform overnight. It will be won by those who continuously increase their capacity to respond.

Closing Loop

The market is always speaking.

Through behaviour.
Through signals.
Through shifts that are often subtle — until they are not.

Most organisations can hear it. At least, in fragments.

The real question is not whether you have access to the signal.

It is whether you are designed to respond to it.

Whether your organisation can:

• Sense at the edge

• Interpret in context

• Act in time

• Adapt in form

And do so not once, but continuously. Because in a world of unpredictable and ever-changing demand. The winners will not be those who predict best.

They will be those who respond best.

And perhaps, more importantly:

Those who are willing to become something different
- as the market itself becomes something new.

Thirty can be described as “3 perfect 10s”. Three is the most creative and expressive force in numerology.

In Hinduism, the Om (Aum) symbol reflects the cycle of life - often associated with the three parts of existence: Brahma, Vishnu, Shiva.

De La Soul (three of them) reminded us that three is the magic number.

Dumas gave us the Three Musketeers (even if D’Artagnan complicated the maths).

In engineering and architecture, the triangle is the strongest shape.

And then there is thirty. 3x10.

Confucius saw thirty as a time of stability - something we could all do with right now.

Across religious texts, thirty appears again and again: as age, as measure, as symbol.

In human life, thirty is not quite a beginning. But nor is it an ending. It is a threshold.

In numerology it equates to: Creation. Expression. Integration.

But 30 is not youthful creativity. It is integration earned through reality.

It is what happens when:

• ideas meet resistance

• models meet systems

• aspiration meets constraint

And for HR, that matters.

30 Years Ago.

In 1996, the world was introduced to the book Human Resource Champions: The Next Agenda for Adding Value and Delivering Results. By Rensis Likert Professor of Business at the Ross School of Business, University of Michigan, Dave Ulrich.

What became known as the “Ulrich Model” for HR was first introduced to the world in 1996, 30 years ago this year.

Recognising this, I wanted to put my own “dent in the universe” with my third book (another 3!) The HR Operating Model and the concept of HR3.0 as an evolved model (3/3.0/30 - you can see a pattern).

And so with the 30th in the Polymorphic Organisations Chronicles, this is all most apt. However, this is not a celebratory post per se.

This is a reckoning.

HR Is Under Pressure - And It Knows It

Let’s start with a dose of reality and be clear as we can without bias (as I am an HR Practitioner by definition/choice/field).

HR is not failing. But neither is it thriving.

Across research and lived experience, we see the same signals:

• Engagement is fragile

• Trust is uneven

• Conflict is rising

• HR professionals themselves are under strain

This quote from People Management Magazine’s feature “HR Under Pressure” is telling from recent research:

Unrelenting

That’s a darned strong word.

And then there’s this one from the same piece:

And Deloitte are unequivocal about this in their feature HR Reimagined from June 2025:

“The core function and value proposition of HR teams…is on the brink of not just significant change but total reimagination.”

Three Brutal Truths About Where HR Is Today

Across all the research, models, and lived experience, three patterns show up again and again:

1. HR is still structurally industrial

Despite digital tools, AI pilots, and rebrands:

• Processes remain reductive

• Systems remain compliance-heavy

• Mindsets remain risk-first

David Liddle in his book People and Culture calls this out directly:

• reductive

• retributive

• infantilising

• divisive

That’s not a future-ready people function; it’s legacy architecture and mindsets tinkering with modern tools.

2. HR is trapped in a paradox without resolving it

Dave Ulrich named the paradoxes, but most organisations are still stuck in them:

• Business vs People

• Strategy vs Operations

• Efficiency vs Experience

Not balancing them, thrashing between them.

3. HR is being outpaced by the very future it is supposed to lead

• AI

• Automation

• Fluid work

• Skills-based models

• Platform organisations

All accelerating, and yet:

• HR adoption is fragmented

• Capability is uneven

• Confidence is shaky

Deloitte’s warning is clear:

HR must move from supporting change to architecting the future workforce

Right now? HR isn’t consistently doing that. It’s not always HR at fault here, because some (many?) business leaders overindex in some areas and overlook others.

So this is not just evolution. This is a fork in the road.

And yet… HR has already been evolving, so it would be wrong to say HR hasn’t moved - it has. But then so has everything else in work, and in many cases, HR hasn’t evolved enough. Both as a profession writ large and inside its contextual home within organisations.

HR 3.0 As A Necessary Shift

When I got the chance to conceive a new HR Operating Model, no one asked me to do that. I had three stimuli for this:

1. Most major consulting firms were attempting to define the next stage of HR Operating Models following the pandemic. And most of those seemed overly complex and somewhat linked to their service offer (!).

2. The Ulrich model was by far the dominant one and yet, we were (at the time of conceiving HR 3.0) 25 years from the introduction of that. Not many organisations seemed to have significantly adapted it. It was showing its age and strain.

3. I’d been named No 1 Most Influential Thinker in HR by my peers through HR Magazine, and I felt an urge to do some bigger thinking in recognition of that. So I designed a new operating model, serialised it in said HR Magazine, and it eventually became a book. Published in August 2025 by Kogan Page.

I came up with the Operating Model and Concept of HR 3.0

HR 3.0 reframed and reimagined the function:

From:

• silos and bureaucracy

• uncertainty on ownership and impact

• process obsession

To:

• People at the centre

• Enabled by Products, Processes, Systems, and Science

It was aiming to make HR:

• more deliberate - human-system interplay; value chains and core impact to create

• more diversified - whilst being evidence-led, science and systems-based

• more dynamic - whilst being better designed for the “turbulent twenties”

  

But even before the book was published, I had a critical realisation:

Even if HR modernises, what if the organisation around it doesn’t?

The real gap and devaluing aspect could be that HR evolves, but the organisation hasn’t/doesn’t. And so we’d see progressive HR thinking operating inside structurally rigid systems, unable to take full advantage of that reimagined people function.

An HR 3.0 function is no good if it sits inside an HR 2.0 Organisation.

This is the friction and tension I felt. And that is where Polymorphism emerged from (initially).

In the People Management piece, I said the following:

From HR 3.0 » Polymorphic Organisations

If HR 3.0 answers: What should HR become? Polymorphism answers: What must the organisation become for that form of HR to work?

This is a shift from function to system. And it has the potential to change everything.

So What IS the Role of HR Now?

Not just a business partner, a people champion or a support function.

HR becomes the designer of the human–system interface. Where people, work, systems, technology, intelligence, and capabilities come together.

HR is no longer a function. It is a People and Culture system-level capability.

Five Roles of HR in a Polymorphic Organisation

1. Workforce Architect (Human + Machine)

Deloitte are clear:

HR must become the architect of the future workforce

Work is now AI-assisted, AI-augmented and increasingly AI-powered.

HR must design what:

• humans do

• machines do; and

• how they collaborate

In HR 3.0, this comes from the spaces of Systems and Science and integrates evidence in multiple forms. With sensing and imaginative responses to work and tasks being redesigned with the advent of automating technologies and complex demands from a world in constant change and turbulence.

2. Capability Engine (Not Job Manager)

Jobs are dissolving. Capabilities are accelerating. Reports and research claim that at least 40% of core skills will change by 2030.

HR must build:

• skills systems

• capability flows

• learning ecosystems

In HR 3.0, this again comes from the spaces of Systems and Science and utilises Product (Design, Ownership, Management) and Processes (more efficient and optimised People Ops through Workforce Planning, Talent Development, People Analytics and work/task design.

3. Systems Designer

Work as a system flows through:
» purpose and meaning » values and principles » behaviours and capabilities » climate and energy » outcomes/impact.

HR designs:

• conditions

• flows

• interactions

Clearly, again, in HR 3.0, this comes from the spaces of Systems and Science which link people sciences (individual psychology) to social sciences and organisational psychology. How we are as unique humans, as collective groups and in a work/business dynamic with multiple forces, protocols, systems, functions. How power, influence, privileges, choice and focus come together with tools, processes and operational energies. In order to build a flourishing enterprise with people who flourish in their work.

4. Organisational Culture and Justice Architect

Culture is not engagement scores. And much of traditional HR investigates, disciplines and escalates.

HR3.0/Polymorphic HR:

• restores

• mediates

• learns

Conflict is not failure. It is feedback. From a system that needs attention whilst seeking justice for people.

A bit repetitive (I know) as in HR 3.0, this again comes from the spaces of Systems and Science (how people cause, relate and act to create culture and when in conflict and unjust situations) and utilises Products (solutions, frameworks, outcome-creating things) and Processes (legal, compliant, fair, just, inclusive and regulatory guidance).

5. Value Assimilator

HR must connect:

• human value

• organisational value

• societal value

Not just performance. But multi-dimensional value creation.

In HR 3.0, this is where we perhaps need the most significant ingenuity and inventiveness. Systems and Science help us with Product (defining, capturing, analysing and reporting on hard-to-catch value parameters/objects) and Processes (how we deploy tools that help us truly know where people value is created in a complex adaptive system and thus, what true value and impact HR has with its interventions, service offers and proposition.

Three Futures of HR

Deloitte offer a helpful framing at this point, although I don’t think it should be read as a prediction so much as a set of plausible trajectories.

What they describe are three broad pathways that HR might follow from here, depending on how it responds to the forces now reshaping work.

The first is what we might call business as usual.

HR continues to evolve, but only incrementally. It adopts new tools, often through vendors, introduces AI in contained ways, and improves what already exists. There is movement, certainly, but the underlying model remains largely intact.

Over time, this path doesn’t lead to failure in any dramatic sense. It leads to drift. And in that drift, something more subtle happens. Other parts of the organisation - technology, operations, even finance - begin to take a more active role in shaping how work is designed and delivered. HR doesn’t disappear, but it becomes less central.

Less influential. More peripheral to the direction of travel.

The second pathway is cost efficiency.

Here, the adoption of AI is more deliberate, more purposeful. Processes are streamlined, service delivery improves, and HR becomes faster and more responsive. This is, in many ways, where much of the current energy sits. Doing the same things, but doing them better. And there is clear value in that. It would be disingenuous to suggest otherwise.

But it is also a path with limits. Because while HR becomes more efficient, it doesn’t necessarily become more important. The function improves, but its role within the system remains largely unchanged. Over time, that often translates into reduction—not just in cost, but in perceived strategic value.

The third pathway is where things begin to shift more fundamentally.

This is what Deloitte describe as value creation, but it might equally be understood as a repositioning of HR within the organisation itself. Here, HR steps forward—not simply to support change, but to shape it. It begins to engage with AI not as a set of tools, but as part of the fabric of work. It takes a more active role in designing the workforce, in understanding how capability flows, and in aligning human effort with organisational purpose in a much more deliberate way. In doing so, it changes its own position—from a function that enables the business, to a capability that helps define how the business actually operates.

Put more simply, although perhaps more bluntly:

- stand still, and you drift;

- pursue only efficiency, and you shrink;

- evolve into dynamic value creation, and you lead/matter more.

What is interesting, though, is that this is not just Deloitte’s view. If you look across the wider field, there is a growing sense of convergence.

Josh Bersin, for example, has been describing a move towards what he calls Systemic HR - an approach that moves beyond services and silos and instead focuses on how the organisation actually functions as a system.

Alongside that, his notion of Full-Stack HR points to the need for HR to operate across the full architecture of work itself - skills, data, platforms, experience - rather than within a bounded functional remit.

And then there is his idea of the Superworker, which, while perhaps sounding a little futuristic at first glance, is really just an acknowledgement of what happens when human capability is meaningfully augmented by technology.

When you place those ideas alongside Deloitte’s framing, and indeed alongside David Liddle’s work on People and Culture, something becomes apparent.

These are not isolated perspectives: they are different ways of describing the same underlying shift.

And, interestingly, they are not a million miles away from what HR 3.0 was already beginning to explore - namely, the idea that HR needs to move beyond structure and process and toward a more integrated, systems-based understanding of how value is actually created through people, aligned to an organisation’s core reason for being and operational impact.

In summary then:

1. Business as usual = irrelevance

2. Cost efficiency = reduction

3. Value creation = transformation

So only one of these survives the likely Polymorphism that all businesses on the planet will adopt to respond to that continuous turbulence in the world.

AI Changes the Game — But Not How You Think

AI is not just automation; it is a redistribution of human effort.

Deloitte show up to 25% capacity can be redeployed. The real question, therefore, is whether HR will use that capacity or lose it.

There has been a tendency, understandably, to frame AI primarily in terms of efficiency. Automation, productivity, cost reduction. All of which are real, and all of which matter. But if we stop there, we miss the more significant shift that is taking place.

AI does not simply remove work; it reshapes it. It redistributes effort, changes the nature of tasks, and alters the balance between human and machine contribution in ways that are still unfolding.

Deloitte suggest that a meaningful proportion of HR activity - around 25% seems plausible here - could be augmented or automated. But that, in itself, is not the most important point.

The more important question is what happens with the capacity that creates.

And capacity is not inherently valuable. It becomes valuable only when it is used differently.

An HR function that is focused on efficiency will tend to absorb that capacity back into the system, doing more of what it already does, but faster.

An HR function that is oriented toward value creation will use it to shift its centre of gravity - toward work that is less about processing and more about interpretation, less about administration and more about design.

This is where Bersin’s idea of the Superworker becomes more tangible.

Not as a distant concept, but as something already beginning to take shape. Individuals, supported by AI, operating with greater reach, making decisions with more information, creating outputs more quickly and with greater sophistication. The constraint, increasingly, is not what individuals can do, but what the system allows them to do.

And that brings us back, again, to HR.

Because if capability is expanding, but organisational design remains static, then the system becomes the bottleneck.

The Bigger Context — A World in Flux

• Geopolitical tension

• Economic volatility

• Climate pressure

• Social expectation

HR must now:

• navigate systems

• interpret signals

• hold complexity

This is not administration: This is stewardship.

All of this is happening within a wider context that is itself becoming more complex. Geopolitical tensions are reshaping markets and mobility. Economic volatility is influencing how organisations invest, hire, and grow. Climate pressures are altering priorities and expectations, often in ways that are still emerging. And social expectations - around fairness, inclusion, purpose - continue to evolve at pace.

These are not distant forces. They are active conditions within which organisations operate. And they are increasingly interconnected.

Which means HR cannot remain narrowly focused on internal processes and practices. It has to develop a more systemic awareness - an ability to understand how these external dynamics translate into internal realities. Dave Ulrich has been banging this drum for a good few years now.

This is where Ulrich’s “HR is not about HR” mantra come into plain sight; and the idea of Systemic HR begins to feel less like a model and more like a necessity. Not because it is conceptually appealing, but because the environment demands it.

In that sense, HR’s role becomes less about managing people and more about helping the organisation maintain coherence under pressure.

About seeing patterns, interpreting signals, and responding in ways that keep the system aligned, even as the conditions around it shift.

As we said just a little earlier, it is, in a word, stewardship.

What HR Must Do Now - Seven Moves

So what does this mean in practice?

Not as a future aspiration, but as something that can begin now. It starts, perhaps, with a different way of looking at work.

Not in terms of roles or job descriptions, but in terms of the underlying activity.

1. What exists because it always has?

2. What no longer needs to exist?

3. What could be reconfigured entirely?

These are not abstract questions; they are practical ones, and increasingly necessary.

Alongside that sits a more deliberate move toward capability.

Away from fixed definitions of roles, and toward a more fluid understanding of what people can do, and how that capability can be applied across different contexts.

This is not new thinking, but it becomes more pressing as the half-life of skills continues to shorten.

There is also a need for HR to engage more directly with AI - not as a technical implementation, but as part of how work itself is designed.

The question is not simply how AI can be used, but how human and machine capability come together in a way that creates value.

At the same time, it may be necessary to reconsider the reliance on policy as the primary mechanism for shaping behaviour. In more complex systems, behaviour is influenced less by rules, and more by the conditions in which people operate. That doesn’t remove the need for structure, but it does change the emphasis.

Similarly, the way organisations respond to conflict may need to evolve. Moving away from purely adversarial processes, and toward approaches that focus on resolution, restoration, and learning. Not because conflict is desirable, but because it is often informative.

There is also something to be said about data. Not more of it, necessarily, but a different relationship with it. Less focus on reporting what has happened, and more on understanding what it might mean—and what it suggests about what comes next.

And finally, there is the question of value. Not just how it is measured, but how it is understood. Because if value is multi-dimensional—and increasingly it is—then HR’s role in interpreting and articulating that becomes more complex, but also more important.

None of this represents a radical departure in isolation. But taken together, it begins to shift the orientation of the function.

From activity to intention. From process to system.

Seven Moves In Summary

1. Redesign work (not just roles) - task intelligence offers us much here at an atomic and systemic level

2. Build capability systems and create more use of individual and collective proficiency plus the emergent shifts in skills

3. Own the design and deployment elements of AI as it pertains to the workforce

4. Replace policy with system design and the maturity of the Employee Value Proposition

5. Rebuild organisational justice and hold the organisation AND its people to account, to each other to build a just and participatory culture

6. Become insight-led and use science where complexity and volatility interfere with the systems of work

7. Measure value differently and much more intricately especially where value is created by people.

In essence, we should stop optimising HR and start redesigning the system it operates in.

HR 3.0 + Polymorphism (Together, Not Separate)

HR 3.0 builds capability. Polymorphism builds the environment where that capability can actually function.

It is important, at this point, to be clear about the relationship between HR 3.0 and Polymorphism. They are not alternatives. They are not competing ideas. They are, in many ways, complementary and need each other.

HR 3.0 provides the Operating Model built for versatility and unleashing new and strengthened capabilities - the thinking, the architecture, the integration of people, products, processes, systems and science.

It offers a way of understanding how a more modern, more intentional People Function should operate.

What it does not do (on its own) is guarantee that the organisation around it is able to support that capability.

That is where Polymorphism comes in.

Not as a model of HR, but as a way of thinking about the organisation itself. One that is more fluid, more adaptive, less constrained by rigid structures, and more capable of responding to continuous change.

In that sense, HR 3.0 builds the upgraded function. Not just the HR team itself, or the professionals within it, but the full scope of what HR does - people, performance, learning, culture, design, experience, reward, wellbeing, development, creativity, relationships, inclusion, and participation.

Polymorphism builds the conditions in which the “people work” can fully function (sustainably) at its imagined and intended best.

Final Reflection

Thirty is not a milestone. It is a point of integration. A moment where ideas, experience, and reality begin to align, or fail to.

HR has evolved, undoubtedly. More scattered, random and not as a prevailing norm though.

So the question now is whether that evolution is sufficient for the environment it finds itself in. Because that environment is changing continuously, and often unpredictably.

And in that context, the question is no longer whether HR has this mythical seat at the table.

It is whether HR can help design the system that upgrades (or replaces) “the table” completely.

Because if it can, it becomes indispensable. If it cannot, it risks becoming optional.

And the power in the number thirty - Creation; Expression; Integration - is where that becomes viable.

MVP meaning not Minimum Viable Product

but

Maximised Visible Performance.

My read is this: By 2029, the biggest risk is not that all young people will be “replaced” by AI. It is that the traditional first rung of the ladder keeps eroding faster than institutions can redesign it.

The emerging pattern is less “sudden job apocalypse” and more “starter work hollowing out”: Fewer classic junior roles, higher expectations on day one, more AI-mediated task execution, and a widening gap between formal education and actual organisational demand.

Working thesis for 2029

If GenAI and early agentic systems keep diffusing at roughly their current pace, then by 2029:

• Early-career work will exist, but less as a bundle of routine tasks and more as a mix of orchestration, judgment, verification, relationship work, contextual problem-framing, and AI supervision.

• Employers will increasingly expect new entrants to arrive with baseline AI fluency already in place, because the old “learn the basics by doing the admin” model is being weakened.

That is already visible in consulting and labour-market research:

1. BCG reports that rising expectations are reshaping entry-level pipelines, with new hires expected to contribute at a higher level from day one.

2. McKinsey sees high-AI-exposure job ads falling faster than low-exposure ads; and

3. LinkedIn projects that by 2030, 70% of the skills used in most jobs will change.

So the 2029 question is not simply “Will there be entry-level jobs?” It is:

Will we still have enough developmental work to turn novices into professionals?

That appears to be the real societal faultline.

1) What academia is actually finding

The most important academic point is that the evidence is now mixed, but worrying in one very specific place: early-career white-collar pathways.

A Stanford/NBER paper using high-frequency ADP payroll data found that early-career workers aged 22–25 in AI-exposed occupations experienced a 16% relative employment decline, with effects concentrated where AI appears to automate rather than augment labour. The same paper also reports a 6% decline in employment for 22–25-year-olds in the most AI-exposed occupations from late 2022 to September 2025, versus growth for older workers in the same occupations. The authors are careful: they say the evidence is consistent with GenAI disproportionately impacting entry-level workers, not that the entire causal story is settled.

Anthropic’s own March 2026 labour-market analysis is more cautious, but still notable. It finds no clear unemployment spike in the most exposed occupations, yet it does find tentative evidence that hiring has slowed slightly for workers aged 22–25 in those professions, and it flags programmers, customer service representatives, and financial analysts as among the most exposed occupations.

At the same time, Humlum and Vestergaard’s NBER paper on Denmark is a useful counterweight. They replicate declines in early-career jobs in exposed occupations, but argue those declines are not explained simply by firm adoption of AI chatbots. They find modest time savings, occupational mobility effects, and little evidence yet of large earnings or hours effects. In other words: disruption is visible, but the mechanism is more complex than “firms bought chatbots, therefore juniors disappeared.”

That balance matters. The academically honest summary is:

There is now credible evidence of starter-job stress in exposed fields, but not yet decisive evidence of universal AI-caused mass youth unemployment.

2) What the big institutions are saying

OECD is now plainly warning (here) that young people face “potential competition with AI for entry level jobs,” and places that warning alongside existing youth labour-market fragility, especially in countries with high NEET rates. This is significant because OECD is not prone to melodrama.

The World Economic Forum is similarly explicit. Its April 2025 analysis says 40% of employers expect to reduce their workforce where AI can automate tasks, while also projecting technology-driven job creation and displacement at the same time. In its later briefing with PwC, the Forum reports that entry-level workers are more curious and excited than worried overall, but still anxious about security and skill relevance.

That combination is crucial. The macro institutions are not saying “no problem.” They are saying:

• the labour market is being reconfigured

• young people are exposed first

• sentiment is not pure fear, but confidence is uneven

• adaptation capacity will decide outcomes.

  ---

3) What consulting firms are seeing inside organisations

This is where the story gets a little more concrete.

McKinsey’s UK analysis says job adverts in high-AI-exposure occupations have dropped more sharply than in low-exposure occupations, and it explicitly warns that young graduates may be facing a triple-whammy:

1. a broad labour market slowdown,

2. a sharper decline in graduate-level openings, and

3. weaker demand in some of the lower-skilled roles that often give graduates their first foothold.

McKinsey’s recommendation is not to freeze early-career hiring, but to reshape work and keep investing in junior talent so the pipeline does not break.

BCG goes further into organisation design. It says AI is redefining work, broadening roles, flattening hierarchies, and redefining the need for junior, coordinator, and manager roles. It also says rising expectations are reshaping entry-level pipelines, because routine tasks are being automated and new hires are expected to contribute at a higher level from day one. Yet BCG does not conclude that entry-level pipelines should vanish; one of its recommended archetypes explicitly says they should evolve, not disappear, supported by intentional development tracks, rotations and AI-enhanced pathways.

PwC’s 2025 AI Jobs Barometer is important because it pushes back against the lazy “AI = pure cost cutting” narrative. It argues companies using AI just to cut staff may miss bigger growth gains, and its data suggests stronger job demand growth in augmented occupations than in more automated ones. In PwC’s entry-level work analysis with the WEF, it also reports that entry-level workers are learning fast, but many doubt how much of their skills base will still be relevant in three years.

Put bluntly, the consulting industry is telling clients two things at once:

First, the junior pipeline is under pressure.

Second, firms that simply eliminate juniors may create a future capability crisis.

4) What labour-market and platform data are showing

LinkedIn’s January 2025 Work Change Report says professionals entering the workforce today are on pace to hold twice as many jobs over their careers as people did 15 years ago, and that by 2030 70% of the skills used in most jobs will change. It also reports a 140% increase since 2022 in the rate at which members add new skills to their profiles. This is not a stable ladder story. It is a fluid, high-churn, skills-first story.

Indeed’s 2025 AI-at-work research takes a similar direction. It argues the main issue is not wholesale replacement, but transformation. Still, its numbers are stark: 26% of jobs posted on Indeed could be highly transformed by GenAI, with another 54% moderately transformed. Then in a separate 2025 labour-market update, Indeed reports that postings with junior job titles fell 7% between August 2024 and August 2025, while senior postings edged up. In software development, only around 2% of postings were junior as of August 2025.

Even where firms are optimistic, they are changing the shape of work. Microsoft’s 2025 Work Trend Index describes the emergence of “Frontier Firms” built around human–AI collaboration and agentic ways of working. Those firms report higher optimism and performance, but that also implies that the normal baseline for work is shifting fast toward AI-embedded execution.

The implication for 2029 is clear: there may be work, but it will not look like the old “do five years of administrative grind before anyone trusts you” model.

5) What industry experts are saying

Industry voices are split between alarm and redesign.

Dario Amodei’s public warning in 2025 - that AI could wipe out roughly half of entry-level white-collar jobs within five years—was deliberately provocative, but it is not wholly detached from the underlying evidence. Anthropic’s own later research is more measured, yet it still identifies exposed occupations and slight slowing in young-worker hiring. So the sensible stance is: Amodei’s headline forecast is not established fact, but the direction of concern is grounded.

Aneesh Raman at LinkedIn has framed the issue as the “bottom rung” of the career ladder breaking. That language resonates because it matches what the organisational data is showing: not necessarily the disappearance of work, but the disappearance of developmental scaffolding. Even business coverage of Raman’s argument leans on LinkedIn’s wider skills data showing more non-linear careers and faster skill churn.

That distinction matters.

The real fear is not only unemployment.

It is deprofessionalisation by omission.

If fewer people get the chance to practice judgment on progressively harder work, we will not just fail the young; we will also fail the future senior/specialist pipeline.

6) What education commentators and innovators are seeing

Education is apparently not asleep here. But it is uneven, and that unevenness is becoming dangerous. Which worries me immensely.

Gallup/Lumina found in 2026 that 16% of college students had already changed their major because of AI’s potential labour-market impact, and many more were factoring AI into enrolment and career choices.

HEPI’s 2026 UK survey found AI use was now near universal among undergraduates: 95% reported using AI in at least one way, and 68% said AI skills are essential for thriving today. But fewer than half felt teaching staff were helping them build those skills for future careers. HEPI’s recommendations are telling:

• structured AI induction,

• curriculum redesign,

• clear guidance,

• better access, and

• staff development.

Jisc reports UK students are worried about employability and want to be “partners not passengers” in AI adoption, with stronger career guidance and fairer support.

The Digital Education Council’s 2025 employer-facing work is one of the sharpest signals. Across employers in 29 countries and 18 industries, 72% anticipated reductions in headcount, and only 3% believed higher education was adequately preparing graduates for an AI-driven future. That is a brutal indictment of the education-to-work handoff.

At the same time, there are live innovations. Northeastern’s College of Professional Studies has launched a comprehensive AI literacy initiative built around guidelines, faculty integration, community practice and student-facing expectations, explicitly saying AI literacy is now central to preparing students for what comes next.

At school level, the EC/OECD-backed AILit Framework is being built to make AI literacy durable, interdisciplinary and globally usable, linked to PISA 2029 media and AI literacy assessment goals.

Governments are moving too. The UK announced in 2026 that every adult would be eligible for free benchmarked AI courses, with an ambition to upskill 10 million workers by 2030, plus funding for tech pathways and graduate traineeships.

So education is beginning to respond.

But the core problem is pace.

Students are already living in the AI future faster than institutions are redesigning for it.

7) So what will entry-level work probably look like by 2029?

Not one thing, but a new pattern.

1. Fewer pure “do the routine stuff” roles

The classic junior analyst, junior researcher, junior developer, junior coordinator and junior content producer roles will be thinned where their core work is summarising, drafting, first-pass coding, pattern extraction or document preparation. That trend is already visible in exposed occupations and in the way firms describe new-hire expectations.

2. More “AI-augmented apprentice” work

The more plausible surviving starter role is not “no-skill assistant” but “AI-enabled junior operator”: someone who can prompt, check, critique, escalate, contextualise, and communicate. That aligns with BCG’s and PwC’s augmentation logic, and with Indeed’s “hybrid transformation” framing.

3. Higher thresholds for entry

Graduates will increasingly be expected to arrive with portfolio evidence, AI fluency, domain familiarity, and proof of judgment. “Train me from scratch” will be less available in many knowledge sectors.

4. More non-linear entry points

Instead of a single first rung, there will be fragmented pathways: project work, micro-apprenticeships, internal marketplaces, hybrid study-work models, sector bootcamps, portfolio credentials, and role clusters rather than neat jobs. LinkedIn’s skills data and the move toward more fluid careers support this.

5. A sharper divide between “prepared” and “unprepared” entrants

Young people with access to AI tools, mentoring, networks, and practical work-based learning will move faster. Those without that support may find the market brutal. OECD, Jisc, HEPI and the Digital Education Council all point to access, readiness and support gaps as major issues.

So by 2029, the danger is not just fewer jobs. It is more selective, less forgiving, more accelerated entry.

8) Why this is especially dangerous socially

Because starter jobs do more than create income.

They create:

• identity

• socialisation

• tacit knowledge

• professional norms

• confidence

• network effects

• upward mobility.

If AI strips out the low-risk, routine, novice-friendly work without redesigning new pathways for learning, then millions of younger people do not just lose jobs. They lose formation.

That is why this matters politically and morally as much as economically. OECD’s warning on youth mobilisation, WEF’s concern about inequality, and Jisc’s call to treat students as partners all point in the same direction: this is becoming a structural inclusion issue.

9) Where Polymorphism gives us an edge

A Polymorphic Organisation does not start with “How do we preserve old jobs?” It starts with:

How do we continually recombine work, capability, technology and human development so the system stays adaptive and humane?

That is exactly the challenge here.

A. Replace the broken ladder with a portfolio of entry pathways

If one bottom rung is disappearing, build many. A polymorphic system can create multiple legitimate entry modes: short-cycle projects, rotational pods, contribution marketplaces, shadow assignments, peer cells, community missions, and AI-assisted apprenticeship tracks.

Instead of one junior job, create a developmental entry ecosystem.

B. Design roles as evolving capability containers, not static job boxes

The old junior role often existed because someone had to do repetitive sub-tasks. In 2029, those tasks will be unstable. Polymorphism allows roles to be defined around capability growth: sense-making, coordination, stewardship, judgment, experimentation, relationship-building, ethical checking, and human escalation.

That means young people are not hired to be “the human version of the admin.” They are hired into growth architectures.

C. Build AI-augmented apprenticeship deliberately

One of the biggest risks is that AI removes the practice reps novices need. Polymorphic design can counter this by making AI part of apprenticeship:

• AI for first draft

• human novice for critique

• peer or mentor for escalation

• team for reflective learning

• repeated cycles that build judgment.

That preserves throughput while still producing professionals.

D. Turn internal labour markets into development markets

A polymorphic organisation can use internal gigs, cross-functional missions and temporary work cells to create the equivalent of old starter work without relying on bloated permanent junior structures. This matters because firms may resist fixed junior headcount, but they still need talent formation.

So the answer is not “bring back 2008 graduate schemes exactly as they were.”
It is: create fluid developmental work at scale.

E. Make “human edge” work explicit

By 2029, the premium will be on:

• contextual judgment

• trust-building

• interpretation

• coordination across ambiguity

• ethical discernment

• system navigation

• live human communication.

Polymorphism is strong here because it already assumes variety in forms, roles and responses. It is a better fit for a world where work is less about repetition and more about intelligent adaptation.

F. Create novice-safe zones

This may be the most important move.

Every polymorphic organisation should have protected spaces where early-career people can practise decision-making, handle bounded risk, and learn with support. Without that, AI will compress experience requirements upward and make “entry” almost paradoxical.

You could call these:

• learning pods

• capability studios

• supervised delivery cells

• shadow-to-steward pathways

• craft labs.

But the principle is simple: protect the formation layer.

G. Reward organisations for producing talent, not just consuming it

A profound 2029 challenge will be that many firms will want “AI-ready” talent without paying to develop it. Polymorphism could push a different norm: measure organisations partly by how effectively they convert novice potential into system value.

That is a strong policy and business argument: the firms that keep talent pipelines alive will have a long-run edge in resilience, succession and innovation. McKinsey and BCG both point in this direction already.

10) A sharper argument for executives and educators

We might frame the core provocation like this:

AI is not just threatening jobs. It is threatening the social machinery by which societies turn educated young people into experienced adults.

And then:

Polymorphic organisation design may be one of the few viable responses because it can multiply entry points, distribute learning, redesign work dynamically, and keep development alive even when routine work is automated.

That feels like the heart of our task here.

11) A provisional 2029 forecast in one “mini-manifesto”

By 2029, early careers will probably be more fragmented, more AI-mediated and less forgiving than they were in the pre-ChatGPT era.

In many sectors, fewer people will start with repetitive junior tasks, because those tasks will be automated, compressed or absorbed into agentic workflows.

The graduates who succeed will be those able to use AI fluently while adding judgment, relational intelligence, systems awareness and contextual thinking.

The organisations that succeed will be those that redesign entry-level work rather than remove it:

• creating AI-augmented apprenticeships,

• fluid role architectures,

• internal talent marketplaces and

• protected developmental pathways.

Without that redesign, societies risk creating not only youth unemployment, but a broken professional pipeline.

12) Bottom line

The evidence does not yet justify saying “millions of young people will definitely be jobless by 2029.”

It does justify saying that the first stage of professional life is being re-engineered right now, that exposed entry-level pathways are already under pressure, and that education, employers and policymakers are behind the curve in redesigning what comes next.

That is exactly where Polymorphism has force:
not as a decorative theory of flexibility, but as a practical answer to a real civilisational design problem.

There is a moment - quiet, almost imperceptible - when a dominant idea stops being inevitable and starts becoming optional.

For well over a century (multiple centuries indeed), the stratified divisional hierarchy has been that idea.

Not just a structure, but a logic. A grammar of organisation so deeply embedded that we stopped seeing it as a choice. Layers, reporting lines, spans of control, cascading objectives. The pyramid is both a map and a metaphor.

And now, something is shifting.

Not abruptly. Not cleanly. But undeniably.

What sparked this post is former Twitter CEO/Founder Jack Dorsey’s recent essay on moving “from hierarchy to intelligence”. It has stirred a particular kind of response in me - part intrigue, part excitement, part unease. It’s found here.

It suggests that what we have long taken for granted as necessary - the layering of authority, the choreography of coordination, the ritual of management - may in fact have been a long-standing and oft-unquestioned contingent. A workaround for a world where information moved slowly, imperfectly, and unevenly.

If that constraint is dissolving, what follows?

This question matters. Not because hierarchy is suddenly obsolete, but because the conditions that made it dominant are changing. And when conditions change, forms follow.

But what replaces it is not obvious. And perhaps more importantly, what should replace it is even less so.

The inherited architecture of control

To understand what might come next, we must first understand what we are leaving behind.

The stratified divisional hierarchy did not emerge by accident. It was an elegant response to a set of very real constraints:

• Information was scarce and slow-moving

• Coordination was costly

• Human cognitive capacity was limited

• Scale required standardisation

The Roman military, often cited as an early archetype, organised soldiers into nested units with clear spans of control. Modern corporations adopted similar principles, formalised through management science in the 20th century. The logic was simple: break complexity into manageable parts, assign accountability at each layer, and ensure information flows up and down in controlled channels.

Middle management, in this system, became the connective tissue. Translating strategy into execution. Aggregating information. Resolving local conflicts. Maintaining coherence.

It worked. Remarkably well.

But it came at a cost.

Over time, coordination became institutionalised as a function. Reporting became ritualised. Decision-making slowed. And the structure itself began to shape behaviour in ways that were increasingly misaligned with the environments organisations found themselves in—dynamic, interconnected, fast-moving, and often ambiguous.

The hierarchy was not just organising work. It was constraining it.

The provocation: from structure to intelligence

Dorsey’s thesis lands with force because it targets the very foundation of this system.

If the primary purpose of hierarchy has been to route information and coordinate activity, what happens when those functions can be performed—faster, more accurately, and at scale—by an intelligent system?

The proposition is radical, but not implausible:

An organisation built not around layers, but around an intelligence layer.

One that maintains a real-time model of:

• what is being built

• what is blocked

• where resources are

• how customers are behaving

And from that, composes work dynamically.

In this model, the traditional managerial role dissolves. Not because leadership is no longer needed, but because coordination as a job becomes redundant.

Instead, three roles emerge:

• Builders

• Problem Owners

• Player-Coaches

Work is no longer passed down a chain. It is assembled, recomposed, and directed through a system that “understands” the organisation in motion.

This is not just a reorganisation. It is a reframing.

The organisation is no longer a structure. It becomes an intelligence.

A familiar echo

For those of us working in the space of organisational evolution, this is not entirely new. It resonates deeply with the direction of travel I have been exploring through the lens of Polymorphic Organisations.

The move away from:

• divisions toward spaces

• roles toward proficiency

• hierarchy toward flow

The idea that organisations are not fixed forms, but adaptive systems capable of reconfiguring themselves in response to changing conditions.

What Dorsey articulates in his essay is, in many ways, an operationalisation of that shift.

Where Polymorphism has been conceptually rooted in systems thinking, developmental psychology, and organisational design, this thesis introduces a technological substrate that makes such fluidity more feasible.

It gives shape to the idea that work can be dynamically composed from capabilities. That coordination need not be human-mediated. That the organisation can, in some sense, “know itself” in real time.

But it also raises deeper questions.

Because if the organisation becomes an intelligence, what happens to judgement?

The counterpoint: hierarchy as sovereignty

This is where a critique of the LinkedIn post that shared this essay from Stefan Norrvall cuts through any unbridled enthusiasm we might have, with some necessary clarity.

Hierarchy, he argues, is not merely a mechanism for routing information. It is a system of sovereignty.

It defines:

• who has the authority to make trade-offs

• how decisions are legitimised

• where accountability resides when things go wrong

This distinction is critical. Coordination can be automated. Information can be aggregated. Patterns can be detected.

But decisions - real decisions, the kind that involve irreconcilable tensions—require something else.

They require judgement. And judgement is not simply the application of data. It is the interpretation of meaning across time horizons, contexts, and consequences.

• When speed conflicts with quality.

• When risk challenges reward.

• When short-term gains undermine long-term viability.

Someone, somewhere, must decide. And not just decide, but own that decision.

This is the part that cannot be abstracted away (when the hierarchy is removed actually, or conceptually).

The shadow that follows removal

There is a second insight in Norrvall’s response that deserves equal attention.

When formal structures of authority are removed without being replaced by something equally robust, they do not disappear. They reappear - informally.

In self-managed systems, we often see this.

• Decision-making becomes diffuse.

• Alignment becomes negotiation.

• Power becomes implicit rather than explicit.

What was once visible and accountable becomes hidden and contested.

The promise of autonomy gives way to the reality of ambiguity.

This is not a post-hierarchy world. It is a poorly designed one.

And it reveals something important:

Hierarchy itself is not the problem.
Unexamined hierarchy is.

Beyond replacement: towards reconfiguration

So we find ourselves in a position between two. One suggests that hierarchy can be replaced by intelligence. The other insists that its core functions - authority, accountability, and judgement - are irreducible.

The question, then, is not which is correct.

It is how they can be integrated.

This is where the Polymorphic Organisation offers a more nuanced path. Not by rejecting hierarchy outright, nor by preserving it in its traditional form, but by reconfiguring its role within a broader system.

The dual-layer organisation

What begins to emerge is a dual-layered model.

On one layer, an intelligence system:

• sensing the organisation in real time

• orchestrating work across capabilities

• providing visibility, coherence, and flow

On another, a sovereignty system:

• defining decision rights

• holding accountability

• integrating judgement across competing demands

These layers are not hierarchical in the traditional sense. They are interdependent.

The intelligence layer informs.
The sovereignty layer decides.

Together, they create a system that is both adaptive and accountable.

The organisation as a learning entity

At the heart of this shift is a deeper transformation. The organisation is no longer defined by its structure, but by its capacity to learn.

“What does your company understand that is genuinely hard to understand?”

This question reframes everything. Because in a world where information is abundant and tools are ubiquitous, competitive advantage lies not in access but in insight.

In the ability to:

• interpret complex systems

• recognise emerging patterns

• integrate diverse perspectives

• act coherently in uncertainty

This is not a technical challenge. It is a developmental one. It requires individuals and collectives capable of operating at higher levels of complexity. And this is where Polymorphism extends beyond what the intelligence thesis alone can offer. Because it recognises that not all actors interpret reality in the same way.

That meaning is constructed, not given.

That the same data can lead to different conclusions depending on one’s developmental stage, experience, and perspective. In this sense, a single “world model” is not enough.

What is needed is a plurality of models, held in dynamic tension.

Polymorphisms for a new era

As we step into this space, new principles begin to take shape. Not as rigid doctrines, but as guiding insights- what we might call Polymorphisms.

“Structure is a temporary agreement with reality.”

“Coordination is a system function, not a human burden.”

“Authority does not disappear—it migrates.”

“An organisation is what it understands, and how that understanding evolves.”

“Without explicit power, you get implicit politics.”

“AI can inform the decision, but it cannot carry the consequence.”

These are not slogans. They are design imperatives.

The deeper shift: from control to coherence

What is really changing is not just the form of organisation, but its underlying philosophy.

The hierarchical model is rooted in control:

• define roles

• assign tasks

• monitor performance

The emerging model is rooted in coherence:

• align around purpose

• enable capability

• orchestrate flow

Control seeks predictability.
Coherence embraces complexity.

And in a world that is increasingly complex, coherence becomes the more viable strategy.

So what is next?

Not a flat organisation. Not an Agentic/AI-run enterprise. Not the total end of hierarchy.

What comes next is a reimagining.

An organisation that is:

• intelligence-augmented, not intelligence-replaced

• fluid in form, but firm in accountability

• distributed in capability, but coherent in purpose

• explicit in power, rather than pretending it does not exist

A Polymorphic Organisation.

One that can change shape without losing integrity.

So what?

It is tempting to treat these ideas as abstract. As something for the future, or for others. But the shift is already underway, and the implications are immediate.

For leaders

The role is changing.

Less about directing.
More about deciding.

Less about managing work.
More about holding the space in which work can emerge.

You are no longer the conduit of information.
You are the integrator of judgement.

The question is not “How do I manage my team?”

It is:

“Where do I need to exercise sovereignty, and where can I let the system flow?”

For organisations

The design challenge is becoming clearer. You cannot simply remove layers and hope for the best. You must design:

• decision architectures

• authority gradients

• accountability mechanisms

At the same time, you must invest in:

• system visibility

• capability mapping

• dynamic orchestration

This is not restructuring. It is rethinking.

For HR and OD practitioners

This is your moment. Because the work is no longer about roles and structures alone.

It is about:

• enabling new forms of coordination

• developing capacity for complex judgement

• designing systems that balance autonomy and accountability

You are not redesigning the org chart.

You are shaping the conditions under which the organisation can evolve.

For all of us

There is a personal dimension. Because as the system becomes more fluid, the demands on the individual increase.

• Clarity of thought.

• Capacity for ambiguity.

• Willingness to take responsibility.

The safety of structure diminishes. The need for maturity grows.

A final reflection

The stratified divisional hierarchy was never the destination. It was a solution. A powerful one, for its time.

But like all solutions, it carries within it the seeds of its own limitation.

What we are witnessing now is not its collapse, but its evolution.

• From structure to intelligence.

• From control to coherence.

• From fixed form to living system.

And in that transition, the question is not whether hierarchy survives.

It is whether we can design what comes next with enough care, enough insight, and enough humility to avoid simply recreating the past in a more sophisticated disguise.

Because the future of organisation is not about removing constraints.

It is about choosing better ones.

And that, perhaps, is the real work ahead.

Post Script: Of course this has all been covered in the excellent work of those behind the Wirearchy here:

https://wirearchy.com/

• Beginning, middle, end

• Past, present, future

• Idea, execution, outcome

And I come at it with this declaration:

I love Product Thinking/Management.

There’s something deeply refreshing about Product Thinking.

For many of us raised in the world of “work as process” - forms, approvals, governance loops, endless cycles of activity - it feels like stepping into sunlight.

In the HR 3.0 Model I introduced in the book The HR Operating Model, Product Management/Thinking gets a lot of props and kudos. It’s a really necessary shift for the People Profession to think and build more like Product Managers than Policy/Programme creators.

Because at its heart, Product Thinking asks a different question.

Not “what do we do?”
But “what do we create that matters?”

It moves us from motion to meaning. From busyness to usefulness. From internal activity to external value.

And that shift is powerful.

But it’s not enough.

Indeed the Polymorphic Organisation (conceptually and into reality) isn’t a product. Part of it is and should be. But it’s more than that: Polymorphism is in itself a complex, adaptive system. In a Polymorphic system, products, platforms, services, and networks coexist and reconfigure, depending on what the moment requires.

Where Product Thinking and Polymorphism share the same philosophy at its heart is this: It’s never finished. It’s, never “done”. It’s always looking for more dynamic ways to create value, have impact, serve its mission, deliver on its promises and stay ahead of whatever other systems throw at it.

So Polymorphism and Product Thinking are like two of the three (four?) Musketeers. The others being Systems and Energy.

So this post is absolutely an homage and honouring Product Management and product thinking. It is, though, a little reminder that inside any system, products will create gains, but will it systemically move things beyond organisation-wide systemic dysfunctions? Not entirely. It’s not designed for that (IMHO).

It’s designed for what it does. Create incredible products.

And to say it will fix everything about the work system being broken is an overreach, and like all other overreaches (Lean, Agile, Matrix, etc.), it’ll get consumed and subsumed within that dominant system.

One which will protect itself unless you can show it a better, more systemic and viable way to evolve.

I want to help Product Thinking become a driving force in reshaping work but it needs some help. So I’m with you Product Thinking. I really am.

It alone has some serious heavy lifting to do. But I believe in it. I know it can be a huge catalyst for wider changes needed to move from the Industrial hangover to a more regenerative age in work.

And Systems Thinking - and in this case my obsession with Polymorphism - is here for that.

From Factories to Features: A Short History of Product Thinking

Product Management didn’t emerge anywhere near to HR, or even from what we now call “knowledge work.”

Its roots sit firmly in industrial capitalism.

• In the early 20th century, companies like Procter & Gamble pioneered “brand managers”- people responsible for the performance of a product in the market.

• Post-war, this evolved into structured product ownership - balancing customer needs, commercial outcomes, and delivery capability.

• Then came software.

And everything changed.

With the rise of Agile, Lean, and digital platforms, Product Management became less about managing a thing - and more about continuously discovering, shaping, and evolving value.

We saw the emergence of:

• User-centred design

• Iterative development

• Outcome over output

• Product-market fit as a living question

Product Thinking became not just a role - but a philosophy.

And rightly so.

Why Product Thinking Feels So Right

At its best, Product Thinking is a rebellion against broken work.

It says:

• Start with the user

• Solve real problems

• Measure what matters

• Learn continuously

• Deliver value, not activity

For HR and People functions, this is pretty intoxicating.

Because it offers an escape from:

• Policy factories

• Transactional service models

• Internal-facing irrelevance

It invites us to build:

• Experiences instead of processes

• Solutions instead of programmes

• Value instead of volume

And that’s a leap worth making.

Here’s the Trap

There’s a quiet assumption creeping in.

That if we just apply Product Thinking to work;

if we just treat “work as a product”

everything will get better.

It probably won’t.

Because Product Thinking, on its own, doesn’t necessarily fix broken systems.

In fact, as Jeff Patton points out in “The Mindset That Kills Product Thinking,” here the danger is when organisations adopt the rituals of product without the mindset.

They:

• Build backlogs instead of insight

• Ship features instead of solving problems

• Optimise delivery instead of understanding value

In other words, they industrialise Product Thinking.

And end up recreating the very thing they were trying to escape.

The System Is the Work

Here’s the deeper issue as I see it:

Most organisations don’t have a product problem.

They have a system problem.

• Work is fragmented across silos

• Incentives are misaligned

• Decisions are too slow or too centralised

• Value is measured internally, not externally

• Complexity is unmanaged

So what happens?

You introduce Product Thinking into a broken system, and the system reshapes it.

• Product teams become mini-silos

• Backlogs become bureaucratic artefacts

• “Customers” become abstract personas

• Delivery pressure overrides discovery

The system wins.

It always does.

Why Product Thinking Alone Isn’t Enough

Product Thinking is brilliant at:

• Focusing attention

• Structuring discovery

• Driving iterative value creation

But it is not designed specifically to:

• Rewire organisational power

• Redesign the flows of work

• Resolve systemic constraints and tensions

• Align enterprise-wide value creation and regenerative energy

It operates within a system.

It does not transform the system all by itself.

And with all the respect to the growing movement that’s underway in the People Profession on Product Thinking, there’s a missing piece. In much of the “Work as a Product” enthusiasm, we may be missing out on applying a powerful lens: That it will still be operating inside a fundamentally flawed machine.

From Products to Systems to Polymorphism

If Product Thinking is big step forward, Systems Thinking is the step change.

It asks:

• How does value actually flow?

• Where are the constraints?

• What patterns repeat?

• What behaviours does the system produce?

It shifts us from:

• Optimising parts » Understanding wholes

• Managing outputs » Shaping dynamics

• Improving work » Redesigning work

• Adapting organisational operating systems » rearchitecting the very nature of how an organisation should operate

But even Systems Thinking isn’t the endpoint.

Because modern organisations don’t just need to understand systems.

They need to adapt across multiple forms at once.

This Is Where Polymorphism Comes In

Polymorphic Organisations go beyond both Product and Systems Thinking.

They recognise that:

• Different problems require different operating logics

• Not all work needs to be treated as a “product”

• Not all systems should be stabilised - some should oscillate

• Value is created through multiple, shifting configurations

In a Polymorphic Organisation:

• Some teams operate as product engines

• Others as exploratory labs

• Others as service platforms

• Others as adaptive networks

All connected. All dynamic. All context-driven.

This is not “Work as a Product.”

This is Work as a Living System of Forms.

So What Should We Do?

Don’t abandon Product Thinking. Good gracious me, that’s the last thing we should do.

But don’t over-index on it either.

Instead:

1. Use Product Thinking to sharpen value creation
Build things that matter. Solve real problems.

That is Product Thinking/Management’s most powerful and endearing element. We need it big time. But it also needs…

2. Use Systems Thinking to understand the environment
Fix flows, not just features.

Because everything is a system. And systems are everything. Product Thinking is a fabulous way to use the system’s energy in a way that really powers a lasting shift.

3. Use Polymorphic Design to evolve the organisation itself
Match form to function. Adapt continuously.

Because the goal isn’t just to become “product-led.”

It’s to become value-creating, system-aware, and form-fluid.

Final Thought

Product Thinking is a necessary evolution. I am here for that.

But it is not the destination. It is a super-propellant towards that next stage in organisational evolution though. I’m convinced and back anyone and everyone who gets behing the Product banner.

Yet, if we mistake it for the answer, we risk embedding a new orthodoxy inside an old system. And we’ve seen how that story ends.

Better instead to see it for what it is:

A powerful tool.
A vital shift.
A doorway into a much more sensory room.

but it isn’t likely to reshape the whole house on its own.

Product Thinking needs help. It needs combinations of actors in its systems and the adjacent systems it needs to influence and operate in.

There, I’ve said it.

Years of conditioning inside enterprise-related focal points of performance and through the desperate attempts from HR to categorise performance (and reward) at an individual level have created the beast we have unleashed on the world: The A Player.

Not an A system, the A player. Well screw the A Player.

LeBron James and Michael Jordan were not only brilliant individuals, when they won games and championships they were part of a system that enabled that to happen.

I love the Detroit Lions. With Calvin Johnson (aka The Megatron) they had one of the most complete Wide Receivers the NFL has ever seen. But he was in a system of poor coaching choices, drafts, gameplans and supporting cast. So he never won a championship (or even a Divisional Title).

The Lions system of old is only just being put right. But do they obsess over Jahmyr Gibbs or Aidan Hutchinson? No. They are trying to build a system of a strong culture, draft choices, supporting cast, operating system and gameplans. And two divisional titles (and a stuttering recent season) have proven they’re not there yet in terms of a Championship; but they’re nearer in the past 3 seasons than in a long, long time. Because under owner Sheila Hemp Ford, Coach Dan Campbell and GM Brad Holmes, they’re building systemic brilliance.

And David Ruffin. One of the most deeply powerful soul voices ever. Was he as brilliant as his ego led him to believe? Not really. Given the Funk Brothers instrumentation, the backing of his fellow Temptations, and the song-writing genius of Smokey Robinson, we got “My Girl”. On his own? Nothing spectacular.

The Motown System produced some incredible moments of musical genius: Marvin Gaye, Stevie Wonder, Diana Ross, James Jamerson, Norman Whitfield, Holland-Dozier-Holland etc etc.

But individually brilliant though they are, Motown was also built on systemic brilliance.

From listening to recordings on a tinny one-speaker in-car radio system, and thousands of recordings never seeing the light of day; to the business-like financial prudence and crossover quality where Black artists of the day were still marginalised in a divided America, and yet hit after hit became their signature for years bought mainly by the White record-buying public.

Systemic Brilliance over Individual Performance.

On Systems, Science, and the Reorientation of Excellence

I read a brilliant post that inspired me to write this: here.

This post showed that there are ideas that don’t arrive as disruption. They arrive as recognition.

This piece - The Myth of Individual Excellence - didn’t so much challenge me as confirm something that has been quietly assembling over years of practice, observation, and reflection.

Because if you spend enough time inside organisations- not just analysing them, but inhabiting them- you begin to sense a fundamental contradiction:

We celebrate individuals.But we depend on systems.

We reward personal excellence. But we rely on collective conditions.

We appraise performance as if it is owned. When in truth, it is produced.

And somewhere in that misalignment, we have misplaced one of the most important truths about work: Performance does not live where we think it does.

The Deep Architecture of Performance

Modern organisational life rests on a powerful assumption:

That excellence is located within individuals.

That performance is a property of:

• Talent

• Effort

• Capability

• Motivation

Contained, measurable, and attributable to a person.

This belief is not accidental. It is reinforced through:

• Performance management systems

• Talent frameworks

• Leadership narratives

• Incentive structures

It is culturally embedded, economically convenient, and psychologically appealing. But from a scientific standpoint, it is fundamentally flawed. Because in any sufficiently complex system, outcomes are not the product of isolated agents.

They are the result of interactions.