There’s a moment, about fifteen minutes into any Future of Work session now, where I ask people how they’re feeling about change. This month it was the same as always: curious, anxious, excited, exhausted - sometimes all four in the same breath. One person typed “curiously excited,” and I loved that so much I wrote it down.

But this time, our speaker Mo Berkner Boyt didn’t let us sit with the feelings for long. She wanted to talk about the biology underneath them.

Watch the Recording

Your Brain Doesn’t Know the Difference

Here’s the sentence that stopped me mid-scroll: our brains don’t distinguish between change happening at work and change happening in our lives. It’s all just change, and change reads as threat. Mo walked us through why — we spend nearly half our waking life in habit loops because habits are cheap, and thinking is expensive. Your brain uses a disproportionate share of your body’s energy, so it defaults to autopilot whenever it can. When something forces you out of that loop — a new tool, a reorg, a “quick sync” that turns into three hours — your brain doesn’t file it as inconvenient. It files it as danger.

That’s not a metaphor. It’s neurology. And it explains something a lot of us have been quietly wondering: why does everyone seem so tired, all the time, even when nothing catastrophic is happening? One attendee put it plainly in the chat: “Burnout at age 25? That is scary.“ Another wrote that the session “lightened the load mentally” just knowing their brain reacts to change as a threat — not a character flaw.

Change Management Is Not the Same Thing as Change Resilience

This was the distinction that made the whole room lean in. Change management is the project plan — the Kotter model, the rollout dates, the “here’s what’s changing and when.” Change resilience is different. It’s whether you, individually, have the skills to move through change without losing yourself in it. And Mo was clear: these are skills, not personality traits. They can be built. They can also atrophy.

She told a story about a merger integration that went so badly two managers nearly came to blows in a parking lot — one team from Wisconsin, one from Georgia, someone’s toolbox literally taped with a note about “not caring how they did it up north.” Looking back with a resilience lens, she could name exactly what had gone missing: emotional regulation, psychological safety, adaptability. Not bad people. Undeveloped muscles.

That reframe matters more than it sounds. So often, when someone resists change at work, we call it an attitude problem. One attendee said it better than I could: “I find that people are not resisting change, they are resisting the lack of control, the things being done to them and being spoken at because most change is badly done.” That’s not cynicism. That’s a diagnosis.

Twelve Skills, Two Buckets

The framework Mo shared — six change resilience skills (emotional regulation, adaptability, problem-solving confidence, optimism, persistence, change literacy and agency) and six human connection skills (social warmth, empathy and listening, conversational engagement, psychological safety, inclusion awareness, inclusion in action) — gave people something a feeling can’t: a place to start. The chat filled with people self-diagnosing in real time. “Strength: adaptability, growth area: optimism.” “C2 is my wheelhouse, C1 needs work.” Someone wrote, “the resilience I have down... the conversational engagement... empathy/listening.... I am impatient lol.“ That kind of honest, funny self-awareness is exactly what this work is supposed to unlock.

The Line That Deserves to Linger

Someone in the chat wrote a paragraph I haven’t stopped thinking about: “People don’t experience the organisation. They experience their leader. The energy, behaviours and priorities that leaders bring to work every day directly influence their teams... The better they understand and manage their own energy, the better equipped they are to support, inspire and create the environment for their teams to perform and thrive.”

That’s the whole session in one comment. Self-awareness leads to self-regulation, which shapes leader energy, which becomes team energy, which becomes sustainable performance. It’s a chain, and it starts with one person deciding to look inward instead of just pushing outward.

Where This Leaves Us

I don’t think this was a session that changed anyone’s life in sixty minutes. I think it did something quieter and maybe more useful: it gave people language. “I’m not resistant to change, I’m exhausted by badly-managed change.” “My empathy skill has atrophied — I can rebuild it.” “My frontline managers are the temperature gauge for the whole building.” Mo said something near the end that I keep returning to — people want hope, not certainty. They don’t need to know exactly where the road goes. They need to believe they can get better at walking it.

If you missed the live session, I’d genuinely encourage you to watch the recording — and if you’re curious where your own C1/C2 skills land, Mo’s team offers a free, anonymous C2IQ assessment with a full report on your strengths and growth areas.

Access The Learning Path

Always human in the lead. Always grounded in practice.
Cheering you on,
~Liza

“Your Story Shows Up Before You Do”

There are conversations that give you more information, and then there are conversations that quietly return you to yourself. Our July Future of Work Monthly Club Meetup was the second kind.

As I listened to Kevin Marius share his perspective on leading yourself before leading others, I found myself thinking about how often leadership is presented as something we perform for other people. We talk about setting a vision, influencing teams, navigating uncertainty, communicating through change, and delivering results.

All of that matters, yes!

Before people experience your leadership, they experience your story.

A story that influences:

• What they fear.

• What they fight for.

• How they respond under pressure.

• What they believe they must prove.

• And whether they can recognize their own worth without waiting for a title to confirm it.

A huge thank you to Shari Collins for consistently bringing incredible guest speakers to our community. Your network is full of brilliant people, your thoughtful facilitation, warmth, and ability to create meaningful conversations are truly something to appreciate - and something I always learn from. Thank you for being such an incredible ambassador for the Future of Work Community, Shari! 🧡

🎥 Watch the recording

I took pages of notes... and honestly, shed a few tears. Here are the three ideas I’m taking with me.. and how I’m putting them into practice.

1. Your story is already leading. So, know what story is driving you.

Kevin shared a powerful reminder: our stories don’t stay at home when we go to work. They influence how we lead, how we communicate, how we respond to feedback, and how we build trust.

This week’s reflection:

• What experience has shaped me the most as a leader or teammate?

• What belief did I develop because of that experience?

• Is that belief still helping me today?
  

⚡ Future of Work Power Move: Ask ChatGPT (or your favorite GenAI tool)

2. Self-awareness is a leadership skill - not a personality trait.

This may have been my biggest takeaway from the conversation: self-awareness isn’t something we’re born with, it’s something we build. Like any leadership skill, it’s a muscle we strengthen over time.

We spend so much time developing technical skills, business skills, and now AI skills. But one of the greatest leadership advantages isn’t another certification or tool. It’s understanding how you show up when things get hard.

When you’re stressed...

• Do you become quiet?

• Do you over-explain?

• Do you avoid conflict?

• Do you rush to solve instead of listening?

Those patterns usually didn’t appear overnight. They were learned somewhere. The more aware we are of them, the more intentional we can become.

⚡ Future of Work Power Move

3. Don’t let AI replace your reflection.

I spend a lot of time thinking about AI and the future of work. And this conversation reminded me that while AI can accelerate our work, it can’t do our inner work, like it can’t decide who you’ll become while working.

That’s still our responsibility. The future of work won’t simply belong to people who know how to use AI. It will belong to people who know themselves.

⚡ Future of Work Power Move

🎥 If you missed the conversation with Kevin, Shari, and the community members. I hope you’ll take some time to watch the recording. It was one of those conversations that stays with you long after it ends.

Always human in the lead. Always grounded in practice.
Cheering you on,
~Liza

Every month, I leave our Future of Work conversations with a page full of notes.

Some are ideas I hadn’t considered before.

Some are practical tips I can’t wait to try.

And sometimes, the best sessions don’t introduce something completely new—they reinforce something you’ve believed for a long time, but through a different lens.

That was this conversation.

This month, I had the pleasure of welcoming Andy Eninger from The Nova Collective to our Future of Work series for a conversation about optimizing time, prioritizing what matters, and using AI to work more intentionally. I also want to give a heartfelt thank you to Scott Zoll. Scott has been an incredible partner behind the scenes, helping shape our work with The Nova Collective at OpenSesame and collaborating with us to bring conversations like this to our community. Partnerships like this are a big part of what makes the Future of Work series so meaningful.

Productivity has a branding problem

On the surface, this session sounded like a webinar about productivity. It wasn’t.

It was really a conversation about leadership.

If you’ve been part of this community for a while, you already know I tend to get a little skeptical whenever someone promises a new productivity hack. We’re surrounded by advice on how to do more, move faster, answer emails quicker, or squeeze one more meeting into the day.

And somewhere along the way, productivity became synonymous with busyness, and busyness isn’t the goal.

What I appreciated about Andy’s approach was that he never framed productivity as doing more. Instead, he framed it as making better decisions about where our attention belongs.

One of the ideas he kept coming back to was the importance of pausing before reacting.

• Before accepting another meeting.

• Before saying yes to another request.

• Before immediately responding to every notification that appears on our screen.

That pause isn’t wasted time. It’s where better decisions begin.

WATCH THE RECORDING

🤖 AI isn’t the answer. It’s the assistant.

As you can probably imagine, this was my favorite part of the conversation. Not because it was another webinar about AI - we have a lot of those!

But because Andy positioned AI exactly where I believe it belongs: not replacing our thinking, but strengthening it.

Throughout the session, he shared practical prompts that immediately made me copy and paste into Gemini because I knew I’d be using them myself.

One that stood out was an AI Time Audit - something so simple, yet incredibly powerful.

Instead of guessing where your week went, Andy suggested asking AI to become your productivity coach.

Try this prompt in your favorite GenAI tool:

I immediately thought back to our conversation a few months ago about designing an Ideal AI-Powered Work Week. This felt like the perfect companion exercise. One helps you design your week. The other helps you reflect on it.

Another prompt I absolutely loved wasn’t about calendars at all. It was about protecting your attention before automatically saying “yes.”

Instead of reacting in the moment, Andy suggested using AI as a sounding board.

Try this prompt:

That one really stayed with me. Not because AI tells us what to do, but because it slows us down long enough to make better decisions.

And yes, there is more y’all! There was another reminder from Andy that I know I’ll be borrowing:

“AI helps you think it through. The conversation is still yours to have.”

That might be one of the healthiest ways I’ve heard AI described.

• Use it to organize your thinking.

• Use it to uncover blind spots.

• Use it to reduce the mental clutter that comes with modern work.

But don’t outsource your judgment. That’s still your job!

That’s exactly the kind of AI conversation I want us to keep having.

🌱 The future of work isn’t about getting faster

As we wrapped up the session, I found myself coming back to something we’ve explored throughout this Future of Work series.

• AI will continue to evolve.

• The tools will become faster.

• The prompts will become smarter.

That part is inevitable. What isn’t inevitable is how we choose to lead.

The organizations that thrive won’t simply be the ones with the latest AI tools. They’ll be the ones whose leaders know when to pause before reacting.

They’ll know how to distinguish what’s urgent from what’s truly important. They’ll protect their teams from unnecessary noise and create space for the kind of thinking, creativity, and connection that technology can never replace.

Because here’s what I believe...

• More intentional.

• More thoughtful.

• More present.

• More connected.

That’s why conversations like this matter.

Not because they give us another framework to memorize, but because they remind us that leadership isn’t built in moments of urgency. It’s built in the choices we make before urgency takes over.

A huge thank you again to Andy Eninger for sharing such practical tools, generous prompts, and actionable ideas with our Future of Work community.

If you missed this conversation, I hope you’ll take some time to watch the recording. I have a feeling you’ll leave with more than a few prompts to borrow. You’ll probably leave with a few better questions to ask yourself, too.

Always human in the lead. Always grounded in practice.
Cheering you on,
~Liza

One HR leader paused and admitted:

“It’s not really a skill gap. It’s the fear.”

That sentence stayed with me because despite all the conversations about AI, automation, copilots, and productivity, what organizations are really navigating isn’t a technology transformation.

It’s a human one.

Our Happy Hour roundtable brought together top leaders from healthcare, transportation, finance, education, nonprofits, manufacturing, and professional services.

Having leaders from different industries and workforces was so great because they shared remarkably similar challenges. We spent less time debating whether AI is coming and more time asking the harder question:

Technology Doesn’t Create Transformation. People Do.

Teresa Smith from UKG opened with research that reframed the conversation. Transformation succeeds or stalls based on three human signals:

• Trust

• Readiness

• Voice

Nearly every executive around the table immediately connected those findings to their own organizations. One HR executive shared that after losing a beloved founder, rebuilding trust became their biggest leadership challenge. Another described how important decisions were communicated only through leadership chains, assuming the message would naturally reach frontline employees. It didn’t, so they changed their strategy and instead of relying on hierarchy, they started communicating directly through in-office flyers, mailings, multiple channels, and constant reinforcement. The realized that trust requires visibility.

One participant said something that deserves to be repeated:

“If you’re not going to act on a survey, don’t send the survey.”

That wasn’t really about surveys. It was about credibility. Employees don’t measure trust by whether leaders ask for feedback. They measure trust by whether anything changes after they share that feedback.

AI Isn’t the Hard Part

One theme surfaced throughout the discussion:

Several leaders talked about employees wondering whether AI meant increased surveillance or whether automation would eventually replace their jobs. Drivers questioned why cameras were being installed, while others worried new tools signaled the beginning of workforce reductions.

What was interesting was that many of the organizations shared the opposite experience. One leader explained how in-cab cameras actually protected drivers by clearing them of customer complaints. Another described how AI-powered HR assistants helped employees get answers faster without waiting on someone from HR. Others talked about automation eliminating repetitive administrative work so employees could spend more time on work that required human judgment.

The conversation wasn’t really about whether AI is good or bad. It was a reminder that people rarely resist technology itself. They resist uncertainty. When leaders communicate the purpose behind AI and demonstrate how it helps rather than threatens people, trust begins to grow.

Learning Is Becoming the Competitive Advantage

My director Paige Bergman built on that conversation by sharing research that pointed to another important shift. She shared the latest research showing that while artificial intelligence has become the top workforce priority globally, it isn’t standing alone. Reskilling, upskilling, and skills-based talent management continue to rank among the highest priorities for learning leaders around the world. And combined they surpass AI.

That says something important.

While every organization will eventually have access to similar AI tools, copilots, and intelligent assistants, what won’t be equal is each organization’s ability to help people build new capabilities, adapt, and keep learning as technology evolves.

One of my favorite moments came during the discussion that followed. As we talked about AI adoption, someone remarked, “It’s not a skill set. It’s a mindset.” We all laughed and joked that it belonged on a T-shirt, but there was real truth behind it.

Paige and I often talk about Skills OS - the idea that skills have become the new operating system for work. Listening to the group, it felt like we were adding another layer to that thinking. Skills matter, but developing them starts with something even more fundamental: a mindset that’s open to curiosity, experimentation, and change.

A Question Worth Sitting With

When it was my turn to present, I asked the group a question that I’ve been thinking about for quite some time.

The room got quiet.

Not because people didn’t have an answer, but because the question changes the conversation. It shifts us away from asking what AI can do and toward asking what only humans and organizations can create.

Your competitors can buy the same AI platforms. They can license the same software. They can deploy the same copilots. They can even prompt AI to analyze your marketing strategy, your customer experience, or your workflows.

But they can’t copy your culture. They can’t replicate the trust you’ve built with your people. They can’t duplicate leaders who create psychological safety, inspire curiosity, or help employees embrace change instead of fear it.

Technology is becoming more accessible every day. Workplace Culture isn’t!

I believe the future of work won’t be won by organizations with the best AI. It will be won by organizations that learn faster, adapt faster, and create environments where people continue to grow long after the technology has become commonplace.

The Iceberg Beneath AI Adoption

Another idea that generated some discussion was something I call the AI Adoption Iceberg.

Organizations often measure AI adoption by how many licenses they’ve purchased or how many people have access to the latest tools. But what they don’t always measure is something much more important: human readiness.

We’ve almost convinced ourselves that everyone is using AI because it’s everywhere we look. Every headline. Every conference. Every LinkedIn post. But the data tells a different story.

That gap fascinated me. We’re acting as if AI adoption is universal when, in reality, many employees are still trying to figure out where they fit in this new world of work.

That’s what inspired me to create the AI Adoption Iceberg.

Above the surface is what we all see - the excitement, the headlines, the demos, and the early adopters posting about the latest AI breakthrough.

Below the surface is where most organizations are actually living. Some employees are quietly experimenting. Some are waiting for permission because they aren’t sure what’s allowed. Some are overwhelmed because they barely have time to do today’s work, let alone learn a new way of working. And some are quietly wondering if AI is preparing to replace them.

The biggest mistake leaders can make is assuming everyone starts from the same place.

The organizations that get this right won’t be the ones that deploy AI the fastest. They’ll be the ones that meet people where they are and help them move forward with curiosity, confidence, and trust.

The Future Belongs to Learning Organizations

As the conversation wrapped up, one message continued to surface.

The future of work isn’t really about AI. It’s about learning.

Technology will continue to evolve. New models will emerge. Today’s favorite tools will eventually be replaced by something better. The organizations that will thrive won’t necessarily be the ones with the most advanced AI strategy. They’ll be the ones that create cultures where curiosity, experimentation, continuous learning, and psychological safety become part of everyday work.

I’m grateful to the UKG team for inviting us to be part of this executive roundtable and for creating a space where leaders could openly share both their excitement and their concerns about the future of work. Conversations like these remind me that while technology may move quickly, meaningful transformation still happens one person, one leader, and one conversation at a time.

Thank you to every leader who generously shared their experiences. I left the conversation with new ideas, fresh perspectives, and even more confidence that the organizations that succeed won’t simply adopt AI, they’ll build workplaces where people never stop learning.

Always human in the lead. Always grounded in practice.
Cheering you on,
~Liza

There was a moment during our Future of Work club meeting facilitated by our expert Sean A. Fisher Sr. when the discussion quietly shifted. At first, we were talking about AI. But by the end, we were talking about people.

And that distinction matters more than ever. As organizations race to adopt AI-powered decision-making, many leaders are asking practical questions:

• Can AI help us make better decisions?

• Can it reduce bias?

• Can it improve consistency?

• Can it help us resolve workplace conflict?

The deeper question that emerged from our conversation was different:

What happens when the data points one way, but our humanity points another? That is where leadership begins.

Conflict Is Not the Problem

One of Sean’s most powerful reminders was simple:

There is no growth without conflict.

That idea immediately resonated throughout the conversation as participants reflected on the challenges of identifying issues, understanding interests beneath positions, and creating psychological safety during disagreement. Too often, we treat conflict as something to eliminate. The better approach is learning how to navigate it.

The organizations that thrive won’t be the ones that avoid conflict. They will be the ones that build the capability to work through it.

The Human Question Behind Every AI Decision

One of the strongest audience reactions came when the discussion explored situations where AI recommendations conflicted with human judgment.

The community repeatedly returned to the same concern:

AI may not have all the context.

Participants pointed out that leaders can be biased, but so can the systems we build. Several comments highlighted that AI often reflects the biases embedded in the data used to train it. Others noted that data itself can be manipulated or incomplete. This wasn’t an anti-AI conversation.

It was a mature conversation. Our members are not rejecting technology. We are asking for accountability. They were asking for context and for wisdom.

Perhaps the most powerful question raised during the discussion was:

“And what if that person was YOU? What would you want?”

That question cuts through every dashboard, every recommendation engine, and every predictive model. Because behind every workforce decision is still a human life.

The Future Belongs to Thoughtful Troublemakers

One of my favorite moments came when participants began discussing the importance of challenging assumptions.

The conversation became playful, reflective, and surprisingly profound.

A participant jokingly declared:

“I want to be a troublemaker.”

We loved it. Because the future may actually require more constructive troublemakers.

People willing to ask:

• Where did this data come from?

• What assumptions are embedded in this model?

• Who benefits?

• Who might be harmed?

• What context are we missing?

In an age where AI can provide answers instantly, leadership becomes less about having answers and more about asking better questions. That may be one of the most important leadership skills of the next decade.

The Mic-Drop Moment

The conversation continually returned to a deceptively simple idea: Technology can support decisions. It cannot replace responsibility.

• AI can analyze.

• AI can recommend.

• AI can predict.

But leaders still have to decide, and they still have to live with the consequences of those decisions.

Because when humans and machines disagree, the real question isn’t who wins. The real question is:

Have we developed leaders capable of listening to both?

If you missed the conversation, I encourage you to watch the recording and join us for future discussions as we continue exploring what human-centered leadership looks like in an AI-enabled world.

Always human in the lead. Always grounded in practice.
Cheering you on,
~Liza

Watch the Recording

A few years ago, most conversations about AI felt speculative.

Today, they feel personal.

AI is showing up in our workplaces, our hiring processes, our performance systems, our communication tools, and increasingly, our decision-making. The question is no longer whether AI will influence work. The question is whether we are prepared to lead responsibly when it does.

That was the heart of our recent Future of Work conversation with Laura Jacobus of Mitratech and Amanda Sessions of OpenSesame, where we explored the tension between AI’s promise and its potential for overreach.

What struck me most wasn’t fear. It was uncertainty.

Not uncertainty about the technology itself, but uncertainty about who remains accountable when technology becomes increasingly capable. As one attendee reflected through survey feedback, the session helped them think more deeply about “AI’s impact to our work.”

The conversation clearly resonated because it moved beyond tools and into something much more human: responsibility.

The Future of Work Is Becoming a Conversation About Human Judgment

One of the most compelling frameworks Laura shared was the evolution of AI from systems that analyze, to systems that create, to systems that act, and increasingly, systems that reason. Each step offers enormous opportunity - but also introduces new ethical considerations.

The discussion explored:

• AI that analyzes employee data

• AI that creates content and communications

• AI-powered autonomous workflows

• AI systems increasingly trusted to support strategic reasoning

The deeper concern isn’t that machines are becoming more capable. It’s that organizations may gradually outsource judgment itself.

When performance management becomes automated, when hiring recommendations are algorithmically generated, when reasoning engines influence strategic decisions, leaders face a new challenge: How do we maintain accountability when decisions happen faster than our governance structures can keep up?

This isn’t a technology problem. It’s a leadership problem.

Governance Is Not About Slowing Innovation

One of the most important ideas from the session was that governance is often misunderstood.

Many organizations hear “governance” and think bureaucracy. But governance is really about clarity. According to the framework presented, AI governance asks three simple questions:

• What should AI do - and not do?

• How do we ensure it behaves as intended?

• Who remains accountable when it doesn’t?

Those questions sound straightforward. In practice, they are some of the most important questions leaders will answer over the next decade.

The organizations that thrive won’t necessarily be the ones adopting AI fastest. They will be the organizations building trust fastest.

The Hidden Tension Beneath Every AI Conversation

Throughout the discussion, another theme kept surfacing. Most people are simultaneously excited and concerned.

• Excited about productivity.

• Concerned about humanity.

• Excited about efficiency.

• Concerned about fairness.

• Excited about innovation.

• Concerned about unintended consequences.

That tension isn’t a sign that we’re failing to adapt. It’s evidence that we’re asking the right questions. As AI becomes embedded into every aspect of work, the most successful leaders will be the ones willing to sit in that tension rather than rush past it. Because ethics isn’t about having all the answers. It’s about creating the conditions for better questions.

We cannot outsource accountability

The future of work will not be defined by how intelligent our technology becomes. It will be defined by how intentional humans remain while using it.

Technology can accelerate decisions. Only humans can determine whether those decisions align with our values.

That distinction may become one of the most important leadership capabilities of the AI era. If you missed the conversation, I encourage you to watch the recording and continue exploring what responsible AI leadership looks like in your organization.

The conversation is just getting started.

Always human in the lead. Always grounded in practice.
Cheering you on,
~Liza

Recently, I completed a training course on AI workslop. I passed the quiz, got the answers right, and then found myself disagreeing with some of the ideas being taught.

Not because the course was poorly designed. In fact, many of the recommendations were practical:

• Give AI clear instructions

• Provide context

• Review outputs before sharing them

• Don’t assume longer responses are better.

All reasonable advice, but the more I sat with it, the more I realized I was uncomfortable with the way “AI workslop” was being framed. Every time I hear the term it seems to imply that the problem lives primarily in the AI, and I’m not convinced that’s true.

Slop Isn’t New.
AI Just Made It Easier to Produce.

The term “AI slop” emerged as people reacted to an explosion of AI-generated content online.

• Low-quality images.

• SEO articles.

• Spam-like social media posts.

• Mass-produced content with little apparent value.

When people talk about AI slop, they’re often referring to the flood of content designed to capture attention rather than create value. We’ve all seen examples: bizarre AI-generated images, clickbait, content farms, and endless streams of content that spread because they’re easy to consume, not because they’re useful.

The concern is understandable, but there is something important we often forget. None of those problems started with AI.

• Long before ChatGPT existed, many of us sat through meetings that could have been emails.

• We read reports full of corporate jargon that said very little.

• We flipped through 100 slide presentations that never arrived at a recommendation.

• We encountered academic papers that used three pages to explain what could have been communicated in three paragraphs.

That was slop too and the difference is that producing it used to require more effort. AI didn’t invent slop. It reduced the cost of creating it and that’s an important point because it changes where we place responsibility.

And the more I thought about it, the more I realized that this isn’t the form of slop that concerns me most. Most people can recognize obvious examples of attention slop.

To me, the Problem Isn’t Prompting.
It’s Human Judgment.

So we hear this all the time now - to avoid AI work slop, you need better prompts. Sometimes they do, but prompting is only one piece of the equation. You can provide excellent instructions and include detailed background information. You can give the AI all the clear, relevant data, and you can still end up with an answer that is generic and disconnected from reality, or strategically weak.

Why?

Because AI is amplifying the quality of human thinking that already exists!

• If our assumptions are weak, AI can scale weak assumptions.

• If our reasoning is shallow, AI can make shallow reasoning sound impressive.

• If we lack expertise in a topic, AI can generate outputs that look credible enough to prevent us from noticing what is missing.

The real challenge isn’t content generation. The real challenge is evaluation.

• Can we tell the difference between something that sounds good and something that is actually useful?

• Can we recognize when an answer is incomplete?

• Can we identify when confidence is replacing evidence?

Those are human skills and they matter more than any prompt expertise!

Strengthen Your Human Judgement

As we move into a future where AI agents, automation systems, and new technologies become increasingly capable, I suspect we’ll keep inventing new labels for low-quality output. But the underlying problem will remain the same. Humans can produce slop without technology.

Our responsibility in the future of work is to think critically about what we create, what we share, and what we choose to trust.

Maybe the future of work isn’t about learning how to avoid AI workslop. Maybe it’s about strengthening the human judgment needed to recognize it.

As someone who works remotely, I spend a lot of time thinking about communication.

Recently, I was completing a survey about workplace communications. One of the proposed solutions to information overload was a centralized weekly digest - a single summary of key updates, decisions, and announcements.

On the surface, it sounds like a great idea.

Fewer messages. Less noise. More efficiency.

But as I reflected on it, I realized something. I don’t think the biggest communication challenge in modern work is that people communicate too much. I think the challenge is that we’re increasingly treating communication as an information management problem when it is also a human relationship problem.

Those are not the same thing.

Information Doesn’t Build Culture.
Interaction Does.

• A weekly digest is excellent for documentation.

• A weekly digest is excellent for alignment.

• A weekly digest is excellent for creating a historical record.

What it is not particularly good at is helping people think together. A strong and healthy workplace culture is rarely built through summaries. Culture is built through interaction.

• A quick slack message.

• A question asked in the moment.

• A spontaneous conversation.

• A clarification before confusion has time to grow.

• A half-formed idea shared before it disappears.

These moments often seem inefficient. They interrupt our workflow. They create notifications. They require attention.

They are also where much of organizational culture actually lives.

The Idea That Never Makes It to the Meeting

One reason this has become more obvious to me is because I work remotely. When you don’t share a physical office, communication becomes the hallway. Communication becomes the water cooler and the chance encounter that would have happened naturally if people were physically together.

I’ve lost count of how many times I’ve had a thought and told myself:

“I’ll bring it up in the next team meeting.”

Then the meeting arrives days later.

The context is gone. The energy behind the idea is gone. Sometimes I’ve forgotten entirely why it mattered.

Other times the issue has already evolved because conversations happened elsewhere and what could have been a thirty-second exchange became a missed opportunity. Not because nobody cared, but because the communication was delayed in the name of efficiency.

The AI Efficiency Trap

This feels particularly relevant right now because we are entering an era where AI can help us summarize almost everything.

• AI can write the meeting recap.

• AI can create the digest.

• AI can consolidate updates.

• AI can reduce the time we spend processing information.

These are real benefits, but there is a danger in assuming that because information has been transmitted, communication has occurred. Information transfer and meaning-making are different activities.

• A team can receive the same update and leave with five different interpretations.

• A digest can tell people what happened.

• A conversation helps people understand why it matters.

The False Choice

Too often, organizations frame communication as a choice between constant updates and centralized summaries.

To me, the problem isn’t communication volume. The problem is information management. I am not an advocate for saying, stop communicating so much. What I do think is that we should keep communicating throughout the week because that’s how people stay connected and build trust. Just make it easier to know what’s important and where to find it later.

Real-time communication

• Slack updates

• Team conversations

• Recognition

• Project updates

• Questions and answers

Weekly digest

• What changed

• Key decisions

• Action items

• Important deadlines

• Links to source material

The digest becomes a memory system, not a replacement for communication. As someone who studies workplace culture separating two things that often get lumped together is important:

1. Information distribution (getting facts to people)

2. Culture building (creating trust, belonging, and alignment)

A weekly digest can help with #1. It cannot fully replace #2.

And the research on remote and hybrid teams suggests that organizations that treat communication solely as information distribution often struggle to maintain connection, trust, and shared culture over time.

Ongoing communication creates connection while documentation creates memory. Remove any one of these and something important gets lost.

The Future of Work May Require More Human Communication, Not Less

As AI makes information easier to generate, summarize, and distribute, the uniquely human part of work may become even more important.

• Questions.

• Interpretation.

• Context.

• Relationships.

• Trust.

• Shared meaning.

These things are difficult to automate because they emerge through interaction. The future of work may not be about eliminating communication in pursuit of efficiency. It may be about becoming more intentional about which forms of communication help humans work better together.

Because culture is not created when information is stored.

Culture is created when people interact around information.

Today, my director, Paige Bergman and I had the opportunity to join Training Industry for a powerful conversation on L&D’s Role in Building Skills-Based Organizations.

Watch the recording here

And the conversation kept coming back to one core truth:

There was a moment in our conversation when the idea landed differently:

Your job title is not wrong. It is incomplete.

That is the tension so many organizations are feeling right now. AI is moving quickly. Jobs are shifting. Expectations are changing. But many of our talent systems are still built around titles, degrees, tenure, and static job descriptions.

And people are so much more than that.

The Invisibility Problem

One of the biggest challenges organizations face is not a talent shortage.

It is a visibility shortage.

We can see job titles. We can see performance reviews. We can see credentials. But we often cannot see the skills, judgment, adaptability, coaching, project experience, creativity, and learning agility sitting just beneath the surface.

AI did not create this problem.

AI exposed it.

The mic-drop moment for me was this:

Hidden potential cannot be developed.

Skills as the New OS

Skills are not just an L&D initiative. They are becoming the connective tissue between learning, careers, talent mobility, business strategy, and organizational resilience.

That is why we introduced Skills OS™: The Operating System for Human Potential.

It is built around three forces:

• Systems make skills visible.

• Culture makes skills trusted.

• Enablement makes skills actionable.

Because skills only matter when they help people grow, help leaders make better decisions, and help organizations adapt faster than change itself.

What This Means for Leaders

The future will not belong to organizations with the most technology.

It will belong to organizations that can identify, develop, and activate human potential faster than change itself.

That starts with one question:

What hidden skills could solve your biggest challenge?

Watch the recording, reflect with your team, and start there.

Always human in the lead. Always grounded in practice.
Cheering you on,
~Liza

This month’s Future of Work Club meetup with Shari Collins and Dr. Helen Abdali Soosan Fagan felt exactly like that. In a time when so many workplace conversations are dominated by speed, optimization, AI disruption, and uncertainty, Helen brought everyone back to something quieter, and far more difficult:

How do we lead in a way that genuinely honors human beings?

Not performatively. Not theoretically. Not through polished leadership language.

But through awareness. Curiosity. Humility. Connection. Resilience. And action.

As attendees reflected on immigration, identity, bias, belonging, healthcare, leadership, and the emotional realities people carry into work every day, one thing became unmistakably clear:

People are hungry for workplaces where they don’t have to amputate parts of themselves just to belong.

And leaders are still learning how to create those spaces.

The Most Powerful Leadership Question Wasn’t “Why?”

One of the most memorable moments from the session came when Dr. Helen shared a story from her work in healthcare.

A Native American family had lost their 12-year-old son and agreed to organ donation. But they requested something the hospital had never allowed before: they wanted a family member present in the operating room during the organ retrieval process.

At first, the request collided directly with institutional policy.

But instead of immediately rejecting it, Helen encouraged the team to ask a different question.

Not: “Why would you want that?”

But: “Help me understand.”

That subtle shift changed everything.

The family explained their spiritual belief that the child’s spirit rested in the heart until the final moment. Having a trusted family member present mattered deeply to them.

And ultimately, the hospital made space for humanity inside a rigid system.

That story lingered long after the session ended because it exposed something larger happening across workplaces right now:

Many organizations are still built to protect process before people.

Yet the future of leadership increasingly requires leaders who know how to pause long enough to understand context, culture, grief, identity, fear, and lived experience.

The leaders who thrive in the next era of work will not simply be the fastest decision-makers. They will be the people capable of holding complexity without immediately retreating into policy, defensiveness, or certainty.

Bias Often Lives in Assumptions We’ve Never Examined

The conversation around immigration and identity created some of the most emotionally resonant moments of the meetup.

Helen shared her story of immigrating from Iran to the United States as a teenager.

Participants reflected on family histories, inherited narratives, hidden identities, and the subtle ways bias shows up in workplaces and communities.

What stood out wasn’t just the vulnerability. It was the honesty.

There was a collective recognition that many of us move through the world carrying assumptions we didn’t consciously choose — assumptions shaped by culture, media, upbringing, organizational norms, and survival.

One participant reflected on how meaningful it is simply to know someone personally whose story disrupts stereotypes.

Another discussed family members hiding their Jewish identity after immigrating from Germany.

Others reflected on the differences between immigrant experiences and the unique systemic barriers Black Americans continue to navigate.

This wasn’t a conversation trying to “solve” bias in one hour.

It was something more important: A willingness to stay present with uncomfortable truths without shutting down.

And honestly, that may be one of the most necessary workplace skills of the future.

The Future of Work Cannot Be Built on Emotional Disconnection

One of Helen’s most beautiful metaphors centered around winter trees.

She described how people who truly appreciate bare winter trees understand that growth is still happening even when nothing visibly blooms.

That idea landed deeply.

Because so many people right now are carrying invisible transformation.

Teams are exhausted. Managers are overwhelmed. Employees are questioning identity, purpose, belonging, and sustainability. Organizations are navigating AI disruption while simultaneously trying to preserve culture and trust.

And beneath all of it is a quieter question:

Will workplaces become more human as technology advances? Or less?

Helen’s framework — Awareness, Curiosity, Connection, Humility, Action, and Resilience — offered something increasingly rare:

A practical reminder that leadership is not just about operational competence. It is relational competence.

The discussion about AI made this especially clear.

Participants acknowledged both the usefulness and limitations of AI tools.

Helen emphasized that wise leaders understand when AI can support efficiency — and when human discernment, compassion, context, and emotional intelligence are irreplaceable.

That distinction matters.

Because the organizations that succeed in the AI era will likely not be the ones that automate the most.

They’ll be the ones that remember people are not machines to optimize.

The Tension Around “Bringing Your Whole Self to Work”

One of the most nuanced conversations of the session emerged around the phrase many organizations now use:

“Bring your whole self to work.”

Shari raised an important tension: Have organizations truly thought through what that actually means?

What happens when people bring grief, trauma, cultural identity, neurodivergence, political tension, or emotional complexity into systems that still reward conformity?

The conversation acknowledged something many employees quietly feel:

Workplaces often celebrate authenticity in theory while punishing it in practice.

And that contradiction creates exhaustion.

What made this discussion powerful wasn’t that anyone claimed to have a perfect answer.

It was the shared recognition that the future of work requires more emotionally mature leadership conversations than many organizations are currently prepared for.

Mic-Drop Moments

“Help me understand.”

“People naturally minimize pain, but leadership requires intentional awareness.”

“The future leaders will be the ones who maintain human connection while using AI as an assistant — not a replacement for thinking.”

“Leadership is like training for a marathon. You cannot just read about it. You have to practice it.”

Final Reflection

This session reminded me that the future of work conversation is not ultimately about technology.

• It’s about humanity under pressure.

• It’s about whether leaders can remain grounded, curious, and emotionally awake while navigating complexity.

• It’s about whether organizations can create cultures where people are treated as fully human instead of endlessly productive.

And perhaps most importantly:

• It’s about whether we can build workplaces where understanding becomes more important than assumption.

Dr. Helen Fagan gave us more than a leadership framework. She gave us a reminder. People have always mattered. The future belongs to leaders who refuse to forget it.

If you missed the conversation, I highly encourage watching the recording and joining future Future of Work Club meetups. These discussions continue to become spaces where thoughtful people gather not simply to consume information, but to make meaning together.

Always human in the lead.
Always grounded in practice.

Cheering you on,
~Liza

Watch the Recording

There was a moment during our recent Future of Work conversation that stayed with me long after the webinar ended.

We asked attendees a simple question:

“What qualities come to mind that make us uniquely human and distinct from AI?”

The chat lit up almost immediately.

Empathy. Curiosity. Connection. Judgment. Creativity. Compassion. Ethics. Presence.

And underneath those responses was something deeper: Not fear. Not resistance. But longing.

A longing to hold onto the parts of ourselves that make work meaningful.

Because while the public conversation around AI often centers on speed, scale, productivity, and disruption, the emotional undercurrent in workplaces right now sounds very different.

People are quietly asking:

Will there still be room for humanity here?

That’s why this conversation mattered.

During the webinar, Stephanie Wagner and Dr. Joanna Hong from Humin reminded us that the future of work is not ultimately a technology conversation.

It is a leadership conversation.

One of the most powerful reframes from the session was this:

“Soft skills are now differentiators.”

Not because technical capability no longer matters. But because as automation expands, deeply human capacities become more valuable — not less.

Empathy. Awareness. Ethical judgment. Relationship repair. Mentorship. Owning outcomes.

These are not “nice-to-have” workplace traits anymore. They are strategic capabilities.

And perhaps even more importantly, they are the things AI cannot authentically replicate.

One attendee shared that what resonated most was:

“The framing of what is important for humans to keep and hold close in the age of AI.”

Another reflected on the relief of realizing:

“We all have similar concerns.”

That comment stayed with me.

Because beneath every organizational AI strategy right now is a very human tension:

How do we embrace innovation without losing ourselves in the process?

How do we create workplaces where efficiency does not replace discernment? Where convenience does not erode connection? Where automation does not quietly weaken our capacity for reflection, ethical thinking, or difficult conversations?

One slide from the session captured this beautifully:

What Must Stay in Human Hands

• Difficult feedback

• Mentoring

• Relationship repair

• Moral judgment

• Owning the outcome

That list felt less like a framework and more like a warning.

Not because AI is inherently harmful. But because organizations can unintentionally automate away the very moments that build trust, accountability, resilience, and belonging.

The future of work will not be shaped only by what AI can do. It will be shaped by what leaders choose to protect.

And that requires intentionality.

The Humin framework challenged participants to:

1. Make space for human judgment

2. Protect the moments AI makes too easy to skip

3. Train the capacities AI can’t replicate

That third point may be the most important leadership mandate of the next decade.

Not just AI literacy. Human literacy.

The ability to navigate ambiguity. To lead with discernment. To hold complexity. To build trust. To regulate emotion. To create psychological safety. To make ethical decisions when there is no obvious answer.

These capacities are becoming central infrastructure for healthy organizations.

One attendee offered thoughtful feedback that also deserves attention:

They noted that many “future of work” conversations still lean toward conventional organizational assumptions and encouraged broader exploration through systems thinking, organizational design, culture, and alternative workplace models.

I appreciated that perspective because it highlights something important:

The future of work is not a fixed destination. It is an evolving design challenge.

And if we are serious about building more human-centered workplaces, we cannot simply layer AI onto outdated systems and call it transformation.

We have to rethink the systems themselves.

The webinar ended with a question that I think every leader should sit with right now:

“What kind of leader, colleague, and organization do you want to be?”

Because the question is no longer whether AI becomes part of our world. It already is.

The real question is whether we are leading that integration intentionally… or being led by it.

And maybe the future of work is not ultimately about protecting humans from AI.

Maybe it is about protecting humans from becoming less human.

If you missed the session, I highly encourage watching the recording and reflecting on the discussion with your own teams. The conversation was practical, honest, thoughtful, and deeply timely.

Always human in the lead.
Always grounded in practice.

Cheering you on,
~Liza

Over the last few years, I’ve found myself increasingly drawn into conversations about AI, workplace culture, trust, governance, and the future of work. After many of my talks, people often ask me the same question:

So I decided to create this living resource guide, not as an academic bibliography, but as a collection of books, research, films, frameworks, podcasts, and thinkers that have genuinely shaped how I understand this moment we are all navigating together.

• Some of these resources are hopeful.

• Some are cautionary.

• Some challenge the dominant narratives around AI entirely.

But all of them, in different ways, ask a deeper question:

The future of work is not only being shaped by technology. It is being shaped by the values, systems, stories, and choices we normalize alongside it. I hope something here helps you think more deeply, ask better questions, and remain connected to your humanity as we navigate this next era together.

Books on AI Ethics, Power, and Society

• Ruha Benjamin — Race After Technology

  • https://www.ruhabenjamin.com/race-after-technology

• Karen Hao — Empire of AI

  • https://www.amazon.com/Empire-AI-Dreams-Nightmares-Altmans/dp/0593657500

• Kate Crawford — Atlas of AI

  • https://www.amazon.com/Atlas-AI-Kate-Crawford/dp/0300209576

• Safiya Umoja Noble — Algorithms of Oppression

  • https://nyupress.org/9781479837243/algorithms-of-oppression/

• Shoshana Zuboff — The Age of Surveillance Capitalism

  • https://shoshanazuboff.com/book/about/

• Meredith Broussard — Artificial Unintelligence

  • https://mitpress.mit.edu/9780262537018/artificial-unintelligence/

• Cathy O’Neil — Weapons of Math Destruction

  • https://weaponsofmathdestructionbook.com/

• Joy Buolamwini — Unmasking AI

  • https://www.penguinrandomhouse.com/books/576618/unmasking-ai-by-joy-buolamwini/

• Liza Mucheru Wisner — Become an AI HERO

  • https://www.amazon.com/Become-AI-Hero-Inclusive-Innovation/dp/1637655096

Books on Leadership, Systems Thinking & Change

• Peter Senge — The Fifth Discipline

  • https://www.penguinrandomhouse.com/books/160902/the-fifth-discipline-by-peter-m-senge/

• John Kotter — Leading Change

  • https://store.hbr.org/product/leading-change/8827

• William Bridges — Managing Transitions

  • https://wmbridges.com/books/managing-transitions/

• Stephen M. R. Covey — The Speed of Trust

  • https://www.speedoftrust.com/

Human Psychology, Trust & Systems Change

• bell hooks — Teaching to Transgress

  • https://www.routledge.com/Teaching-to-Transgress-Education-as-the-Practice-of-Freedom/hooks/p/book/9780415908085

• Paulo Freire — Pedagogy of the Oppressed

  • https://www.bloomsbury.com/us/pedagogy-of-the-oppressed-9781501314131/

• Amy Edmondson — Research on Psychological Safety

  • https://www.hbs.edu/faculty/Pages/profile.aspx?facId=6451

• Zoe Weil — The Solutionary Way

  • https://humaneeducation.org/books/the-solutionary-way/

• Jonathan Haidt — Research on attention, trust, and social connection

  • https://jonathanhaidt.com

• Everett Rogers — Diffusion of Innovations

  • https://books.google.com/books/about/Diffusion_of_Innovations.html?id=9U1K5LjUOwEC

AI Governance & Responsible AI Reports

• NIST AI Risk Management Framework

  • https://www.nist.gov/itl/ai-risk-management-framework

• Singapore Model AI Governance Framework

  • https://www.imda.gov.sg/resources/press-releases-factsheets-and-speeches/factsheets/2020/model-ai-governance-framework

• AI Verify Foundation

  • https://aiverifyfoundation.sg/

• Microsoft + LinkedIn Work Trend Index

  • https://www.microsoft.com/en-us/worklab/work-trend-index

• Federal Reserve AI Workplace Adoption Research

  • https://www.federalreserve.gov/econres/notes/feds-notes/measuring-ai-uptake-in-the-workplace-20240205.html

• MIT Sloan AI Productivity Research

  • https://mitsloan.mit.edu/ideas-made-to-matter/productivity-paradox-ai-adoption-manufacturing-firms

• IMF — “AI Will Transform the Global Economy”

  • https://www.imf.org/en/Blogs/Articles/2024/01/14/ai-will-transform-the-global-economy-lets-make-sure-it-benefits-humanity

• Stanford GSB — Zillow algorithmic collapse analysis

  • https://www.gsb.stanford.edu/insights/flip-flop-why-zillows-algorithmic-home-buying-venture-imploded

• Karen Hao — AI labor and power concentration

  • https://www.technologyreview.com/author/karen-hao/

• Kate Crawford — environmental and infrastructural cost of AI

  • https://katecrawford.net/

• IMF / Kristalina Georgieva — AI’s labor market impact

  • https://www.imf.org/en/Blogs/Articles/2024/01/14/ai-will-transform-the-global-economy-lets-make-sure-it-benefits-humanity

Films, Culture & Human Futures

• Hidden Figures — Katherine Johnson and human trust in technology

  • https://www.imdb.com/title/tt4846340/

• The Social Dilemma

  • https://www.thesocialdilemma.com/

• Coded Bias

  • https://www.codedbias.com/

• AlphaGo

  • https://www.imdb.com/title/tt6700846/

• Ex Machina

  • https://www.imdb.com/title/tt0470752/

• The Great Hack

  • https://www.netflix.com/title/80117542

• Citizenfour

  • https://www.imdb.com/title/tt4044364/

• Minority Report

  • https://www.imdb.com/title/tt0181689/

• Black Mirror

  • https://www.netflix.com/title/70264888

• Her

  • https://www.imdb.com/title/tt1798709/

• WALL-E

  • https://www.imdb.com/title/tt0910970/

• The Danger of a Single Story — Chimamanda Ngozi Adichie

  • https://www.ted.com/talks/chimamanda_ngozi_adichie_the_danger_of_a_single_story

• Interstellar

  • https://www.imdb.com/title/tt0816692/

• Everything Everywhere All at Once

  • https://www.imdb.com/title/tt6710474/

• Blade Runner 2049

  • https://www.imdb.com/title/tt1856101/

• Tristan Harris — Humane Technology

  • https://www.humanetech.com

• Ruha Benjamin TED Talk

  • https://www.ted.com/speakers/ruha_benjamin

• Brené Brown — Vulnerability & Leadership

  • https://brenebrown.com/videos/

• Sam Altman Conversations on AI

  • https://openai.com/news/

• Fei-Fei Li — Human-Centered AI

  • https://hai.stanford.edu/people/fei-fei-li

Podcasts and Thought Leaders

• Brené Brown

  • https://brenebrown.com/podcast-show/unlocking-us/

• Ezra Klein AI Interviews

  • https://www.nytimes.com/column/ezra-klein-podcast

• Hard Fork Podcast

  • https://www.nytimes.com/column/hard-fork

• TED AI Episodes

  • https://www.ted.com/topics/artificial+intelligence

• MIT Technology Review AI Coverage

  • https://www.technologyreview.com/topic/artificial-intelligence/

• Kara Swisher Interviews

  • https://www.voxmedia.com/podcasts/pivot

• OpenAI

  • https://openai.com/news/

• Anthropic

  • https://www.anthropic.com/news

• Human Centered AI — Stanford HAI

  • https://hai.stanford.edu/

• Tristan Harris & Center for Humane Technology

  • https://www.humanetech.com/

• All-In Podcast

  • https://www.allinpodcast.co/

• McKinsey AI Insights

  • https://www.mckinsey.com/capabilities/quantumblack/our-insights

• World Economic Forum — AI & Future of Work

  • https://www.weforum.org/topics/artificial-intelligence/

• Future of Life Institute

  • https://futureoflife.org/

• Partnership on AI

  • https://partnershiponai.org/

One thing I continue learning through all of this:

It is a human conversation.

• About trust.

• About power.

• About labor.

• About dignity.

• About belonging.

• About who gets included in the future we are building together.

And while AI may transform how we work, I hope we never lose sight of the people underneath the systems. Intelligence alone has never determined the future of humanity. Our values do!

What happens when we stop talking about AI like a headline, and start talking about it like a lived experience?

When the buzzwords quiet down and the pressure to sound “ahead” disappears, people finally say what they’re actually thinking. That’s what happened during this month’s Future of Work Club Meetup: AI Reality vs. Hype, led by our club facilitator and host Megan Ysassi.

We didn’t have a panel full of predictions. And it was not another “AI will change everything” discussion.

Instead, it became something far more valuable: A room full of people trying to make sense of what it means to learn, adapt, lead, and stay human while technology moves faster than our comfort levels.

And honestly? That felt refreshing.

One participant captured the emotional tension perfectly:

“We adults have a lot of difficulty diving into things that we don’t have confidence in. The fear of failure is real and holds people back.”

That sentence lingered with me long after the session ended.

Because beneath all the AI conversation right now is something deeper: People are not just trying to learn new tools. They’re trying to learn how to trust themselves again in unfamiliar territory.

The Gap Between Knowing and Doing

One of the most powerful moments from the session came from a simple distinction shared by Megan Ysassi:

Competency vs. Skill.

Theory says:

“I’ve read the manual.”

Practice says:

“I’ve done it.”

That landed deeply with the audience because it named something many leaders and teams are quietly experiencing.

We are surrounded by AI information. Articles. Think pieces. LinkedIn hot takes. Podcasts. Tool demos. Fear. Excitement. Noise.

But information alone doesn’t create confidence. Practice does.

The room became noticeably more energized when participants started sharing how they are actually using AI today — not in abstract strategy decks, but in real life.

Someone shared they use AI to improve grammar and sentence structure before expanding into SOP drafting and executive briefs. Another participant talked about exploring AI as a newly practicing coach. A government employee raised concerns about balancing AI adoption with PII protection and accuracy. A nonprofit leader reflected on the environmental and sustainability implications of AI at scale.

None of these comments were performative. They were practical. Human. Grounded.

That’s what made the conversation powerful.

The future of work isn’t being shaped by people pretending to have all the answers. It’s being shaped by people willing to practice in public.

The Quiet Shift Happening Inside Organizations

One theme surfaced repeatedly throughout the meetup:

People don’t necessarily need permission to hear about AI anymore. They need permission to experiment with it safely.

That distinction matters.

For many organizations, the barrier is no longer awareness. It’s psychological safety.

Several participants spoke openly about fear:

• Fear of getting it wrong

• Fear of relying on inaccurate outputs

• Fear of exposing confidential information

• Fear of sounding uninformed

• Fear of becoming irrelevant

And yet, in the middle of those fears, there was also curiosity.

One participant shared:

“Equipping people to understand that they are still the ‘brain’ in the transaction.”

That may have been one of the biggest mic-drop moments of the conversation.

Because despite the hype cycles, what people are truly looking for is not replacement. They are looking for partnership.

Human + AI. Not human or AI.

That message resonated deeply across the discussion. In fact, another attendee reflected:

“I liked the message yesterday about human + AI. Human first.”

That “human first” mindset feels increasingly important right now. Especially in a moment where many workplace conversations about AI are still dominated by productivity narratives instead of human capability narratives.

The people in this session weren’t asking: “How do we automate everything?”

They were asking: “How do we learn without losing ourselves?”

That’s a very different conversation.

Practice Is Becoming the New Leadership Skill

One quote from the presentation stayed with me all day:

“We learn who we are in practice, not in theory.” — Herminia Ibarra

That line became the emotional backbone of the entire meetup.

Because AI adoption is not just technical. It’s behavioral. Relational. Identity-based.

People discover their confidence through use. Not observation.

And perhaps that’s the larger leadership challenge emerging right now.

The organizations that thrive in this next era may not be the ones with the biggest AI budgets. They may be the ones that create the safest environments for experimentation, reflection, learning, and adaptation.

Not hype. Practice.

Not performative innovation. Meaningful application.

Not fear-based urgency. Human-centered capability building.

That’s the real future of work conversation.

And judging by the energy in this meetup, people are craving spaces where they can explore that honestly.

If you missed the conversation, I highly recommend watching the recording and reflecting on this question we explored together:

“What are you actually using AI for today — not what’s planned, but what’s really happening?”

Sometimes the most important innovation conversations begin with truth instead of expertise.

And maybe that’s exactly where meaningful transformation starts.

Always human in the lead.
Always grounded in practice.

Cheering you on,
~Liza

This week’s Future of Work session with Lisa Bodell was one of those moments. Not because we talked about AI. But because we stopped talking about AI the way everyone else is.

The Real Question Isn’t About Automation

We’ve spent the last few years asking:

• What can AI do?

• What should we automate?

• How fast can we move?

Useful questions. But incomplete, because they focus on execution, and execution is rapidly becoming the least constrained part of the system.

The more important question is this:

What happens when execution is no longer the bottleneck?

Or more directly to this webinar:

Who are we required to become when AI does more of the doing?

AI Doesn’t Remove Leadership. It Relocates It.

One idea kept surfacing for me throughout the conversation:

AI doesn’t eliminate leadership. It makes it visible.

Your leadership is being revealed - whether you’re ready or not.

• When output is instant…

• When analysis is abundant…

• When execution is no longer the constraint…

The pressure moves upstream from doing the work to deciding what work is worth doing at all. And!!! That’s where many leaders are about to feel exposed, because what’s left isn’t task management. It’s:

• Prioritization under abundance

• Decision-making under uncertainty

• Clarity when information is infinite

• Accountability when outputs are co-created

AI can support these. It doesn’t absolve you of them. If anything, it sharpens the consequences.

AI won’t eliminate bad leadership. It will scale it. #ForbesCouncil

Faster Broken Work Is Still Broken

Another ongoing thread that still needs more attention:

We’re not overwhelmed because we lack tools. We’re overwhelmed because of the work of work - the layers of unnecessary complexity, outdated processes, and invisible friction that have built up over time.

AI can remove some of that, but most organizations won’t redesign the system. They’ll accelerate it. Which means we risk doing the same misaligned, low-value work, just faster, and at greater scale.

And that’s not transformation. That’s amplification.

The Misread on “Human-Centered”

Lisa said something that stopped me in my tracks:

“Right now, we are using massive amounts of energy for AI to process stuff… and in the future… one of the biggest costs to companies is energy. And so people are going to really start to… decide what AI shouldn’t do… because we’re using massive amounts of energy for AI to do something that the human brain could do much more cheaply… and quickly sometimes.” ~Lisa Bodell

That point matters more than we’re giving it credit for. AI is not always the better option. In some cases, it’s more expensive - and less efficient - than human thinking.

Which challenges a bigger assumption I keep hearing: That being “human-centered” somehow lowers the bar. Slower. Softer. Less rigorous.

I don’t buy that. In my experience, the highest-performing teams aren’t doing more.
They’re actually doing less more intentionally.

• Unnecessary work is removed.

• Priorities are clear.

• People aren’t waiting to be told what to do - they own decisions and move.

That’s not soft. It’s disciplined. And when you layer AI into that kind of environment - intentionally, not just everywhere - you don’t slow down. You remove friction that shouldn’t have been there in the first place.

Lisa said this PERFECTLY:

“Work was designed for the industrial age… it created a lot of information and processes that were good for machines. And humans became machines. We became cogs. And now… AI is taking the work off our plate that we shouldn’t have been doing in the first place.” ~Lisa Bodell

What a mic drop moment! I’ve seen first hand how much time gets lost in rework, second-guessing, and unclear ownership. AI doesn’t fix that by default, but in the right system, it exposes it and helps you clear it.

And when that drag is gone, what shows up isn’t just more capacity. It’s better decisions. This is where ‘human-centered’ leadership actually lives.

AI Is Exposing the Leaders Who Can’t Decide What Matters

AI is already increasing the gap between good leadership and bad leadership. Lisa touched on this brilliantly!

Leaders who can’t articulate:

• what matters

• what doesn’t

• and why,

will become bottlenecks in a system that no longer needs them for execution.

And organizations that don’t rethink how decisions get made will not fall behind because they missed AI. They’ll fall behind because they automated without redesigning.

What I’m Sitting With After This Webinar

I didn’t leave this session thinking about tools. I logged off thinking about my own leadership responsibility.

We are not being asked to compete with AI. We are being asked to lead in a system where execution is cheaper, speed is higher, and ambiguity is amplified.

And that changes the standard.

It means we can’t hide behind so called ‘activity’ and ‘task completions’.
We have to be sharper in what we prioritize, clearer in how we decide, and more intentional about where we add value.

Because when the doing gets easier… the thinking gets exposed!

If You Missed It

This is a session worth going back to.

Not to capture more information. But to interrogate how you’re operating.

👉 Watch the recording here: https://www.opensesame.com/event/the-future-of-work-leading-thinking-and-deciding-when-ai-does-the-doing

One Question to Take With You

If execution is no longer the constraint - what decisions are you uniquely accountable for… and are you actually equipped to make them? (be honest with yourself!)

That’s where the real shift is happening.

Always human in the lead. Always grounded in practice.
Cheering you on,
~Liza

• No notification.

• No external pressure.

• No obvious reason to stay.

And yet, you do.

That experience, subtle, frictionless, and surprisingly persistent, points to something deeper than convenience. It reflects a growing reality: AI systems are not only useful, but increasingly compelling to engage with.

This raises an important question: what exactly creates that pull, and what are its implications for how we think, work, and relate to one another?

Is AI Becoming Addictive? ...»

Because calling AI ‘addictive’ immediately brings up intent, like someone, somewhere, sat in a room and said: “Let’s make this impossible to put down.”

Now… let’s pause. Because reality check - we’re not naive - we all know large tech companies absolutely can and some do design for addiction. We’ve seen it with social media, streaming platforms, and the broader attention economy. So let’s not pretend that incentive structures don’t exist. They do. And they matter.

But here’s where, for me at this moment of my research, it gets more complex. I have been thinking about the opinion that not all AI systems are being built with the same primary goal. Many are designed for productivity, problem-solving, and task completion - not just attention capture.

And yet… the same forces that made other technologies addictive are still present. It is happening to me!

• Amazing Frictionless design

• Rapid feedback

• Continuous availability

So even without a singular, explicit goal of addiction, we have ended up with AI tools that can feel just as hard to step away from.

So, for this paper, the question isn’t just: “Are companies designing for addiction?”

It’s also:

“What happens when systems designed for usefulness operate inside environments that reward engagement and lead to addiction?” ~Liza Mucheru Wisner

The Real Story: It’s Not Addiction. It’s Friction

For me, AI didn’t win me over by being flashy. It won by being simply easy.

• Need help writing? Done.

• Stuck on an idea? Here you go.

• Not sure what to say? Try this.

No waiting.
No awkward Googling.
No let me ask a friend or mentor.
No ‘let me figure this out first.’

Just… answers.

Behavioral scientist BJ Fogg has a model that explains this beautifully. He says behavior happens when three things come together:

• Motivation

• Ability

• A prompt

And here’s the key. Ability (ease) matters a lot. When something becomes easier to do, we do it more. AI has taken tasks that used to require:

• Time

• Effort

• Cognitive strain

…and made them almost frictionless. And that’s the magic, but it’s also the risk.

When Easy Becomes Automatic

Let’s be clear: reducing friction is a hallmark of good design. It allows users to act efficiently and lowers unnecessary barriers to action. However, when friction approaches zero, a subtle but important shift occurs.

Deliberate choice begins to erode.

Instead of asking: ‘Should I use this?’, users begin to default to ‘Why not?’

I noticed this the other day. I had a simple thought I could’ve worked through on my own. Nothing urgent, nothing complex. And before I even gave myself a moment to think… I opened GPT.

Not because I needed it, but because it was there. Fast. Easy. Ready.

And I caught myself thinking: Oh… we’re not even pausing anymore. That’s what led to this consideration you are reading.

It is clear that over time, that matters. Because effort used to slow us down just enough to reflect, to question, and to wrestle a little.

Now? We can move from question to answer in seconds. And when that happens consistently, we don’t just move faster, we think differently.

You can see this showing up in what people casually call ‘AI slop’, content that’s produced quickly, consumed quickly, and rarely questioned. But this isn’t just a quality issue. It’s a behavioral signal. When the cost of creating and consuming information drops to nearly zero, the incentive to evaluate that information drops too.

And that’s the deeper shift. The risk is that we stop pushing back. We stop thinking critically, which is like a muscle. Use it or lose it!

• We stop refining as much.

• We stop questioning as much.

• We stop sitting with things long enough to develop judgment.

Because why would we? If you’ve been using generative AI long enough - especially with memory - it starts to feel like it knows you. Your tone. Your patterns. The way you think. And that’s where things get interesting.

I noticed this a while back. I asked GPT to review a paragraph I had free-written, something I actually felt good about. And it came back quickly and said, essentially, this doesn’t sound like you.

I paused and then laughed out loud, because part of me thought, “Wait… how are you now telling me what I sound like, when I am the one who just wrote this?” LOL!

Now, to be clear, I kept what I wrote. I liked it. It felt like me. But that moment stayed with me. Not because the feedback was wrong, but because it was immediate. Confident. Frictionless. No pause. No pushback. No time to reflect.

Just an answer that it was not me. To me, this is something worth noticing.

Why It Feels So Good (And Why That Matters)

If you’ve ever used AI and thought:

• Wow, that was fast.

• That actually helped.

• That’s better than I expected.

That’s not accidental.

Nir Eyal’s Hook Model explains how habit-forming systems work:

• Something triggers you

• You take a simple action

• You get a reward

• You come back again

AI fits this pattern almost perfectly. But here’s where I want to be careful:

I don’t thing Gen AI is like TikTok addiction.

It’s not designed (at least not primarily) to trap your attention. It’s designed to help you complete tasks. Which makes this even more interesting. Because the pull we feel isn’t coming from distraction. It’s coming from usefulness.

So… Is It Actually Addiction?

Not necessarily.

Psychologist Adam Alter makes an important distinction. A habit becomes an addiction when you lose control and you keep going despite harm.

Right now, most people using AI aren’t there, yet. They’re just using something that works. But the conditions that can lead to over-reliance are definitely present:

• Instant feedback

• High-quality responses

• Constant availability

And that’s worth paying attention to.

The Part We Don’t Talk About Enough: Incentives

Here’s where things get real. Even if AI companies say they are building for productivity. They’re still operating in systems that reward engagement, usage, and growth. And when those are the metrics, products tend to evolve in a certain direction. Not because anyone is evil, but because incentives shape outcomes.

As Tristan Harris and others have pointed out, technology doesn’t just reflect intention, it reflects business models. So even without trying to create addiction,
systems can drift toward deeper engagement. That’s not a conspiracy. That’s a pattern.

Why Not Just Make AI Less… Compelling?

You could. You could slow it down. Add friction. Make it less conversational.

But then it wouldn’t be as useful. And that’s the tension. The same things that make AI valuable also make it hard to disengage from. So this isn’t really a question of good versus bad. It’s a design tradeoff.

What This Means for Us, Humans

For me, this isn’t just about usage today. It’s about what happening to us over time.

When AI becomes the fastest path to writing, thinking, and problem-solving, we start to offload more of those processes.

Sometimes that’s helpful but it is also a little concerning.

Nicholas Carr warned us about this years ago (2013): What the internet is doing to our brains - The Shallows.

We’re seeing a similar shift. Not because AI is harmful, but because it’s efficient, and efficiency changes behavior.

Now to add more layers to this onion, there is the social layer. This is where it starts to matter a little more. What do we do when the ease starts to replace us, our humanity?

Because let’s be honest, AI is easy to talk to.

• It’s responsive.

• It’s patient.

• It doesn’t interrupt.

• It doesn’t judge.

(If only group chats, team meetings, and… life worked like that, right? JK)

And that’s part of the point!

But we know that human relationships are a completely different experience. From my personal experience, they take attention, effort, require the friction of misunderstandings and require repair to grow strong. A frictionless relationship becomes boring. You don’t just say something to a human and get a perfectly structured response back in two seconds. You have to sit in the pause. You have to clarify. You have to navigate tone, emotion, context.

And that’s not a flaw. That’s the work of being a productive ‘human’ in society.

In this MIT book, Sherry Turkle describes this as the illusion of companionship without the demands of relationship. AI can make us feel heard, but it doesn’t require us to do the things that build connection, and that distinction matters, especially when we think about development.

The human skills I care most about are empathy, boundaries, conflict resolution, and emotional awareness. From my personal experience, those don’t come from frictionless interaction. They come from being wrong and getting corrected, being misunderstood, working through tension and repairing something that didn’t land. That’s how we learn how to BE with other people.

So the question isn’t whether AI replaces relationships. It’s more subtle than that: What happens if we just have fewer of those moments? Fewer misunderstandings, negotiations and chances to sit in the discomfort long enough to grow.

And if we start preferring that layer of AI interaction, not consciously, just habitually, we may not lose our human relationships all together, but we may lose some of the practice required to sustain them.

Which brings me to education. I have three young boys in school.

For me the question about AI in Education isn’t, should we allow our kids to use AI? That’s already answered.

The better question is:

“How do we use AI without losing the kinds of experiences that actually develop our human skills? ~Liza Mucheru Wisner

For me, this question captures the central tension I am feeling, but it requires further specification. The issue is not simply the use of AI, but how its frictionless nature may displace the processes through which cognitive and social abilities are formed.

One way to think about this is preserving what we can call developmental friction. Not unnecessary difficulty, but the kind of challenge that actually shapes us.

For me, the goal isn’t to reject AI. It’s to figure a way for my workflows, to make sure that its convenience doesn’t quietly replace the very things that make me socially capable.

At the end of the day, this isn’t a technology problem. It’s a human one. Ease is powerful, but becoming fully human has never been easy.

If we start preferring AI interactions because they’re easier, what happens to our ability to navigate real ones? Especially for our youth in their formative years?

Final Thought for the Future of Work

AI is not addictive in the traditional sense. It is simply very effective at removing friction. And when effort disappears, reliance tends to follow. The real question is not whether AI is seductive, but what that seduction does over time. Does it extend our capabilities, or quietly replace the very processes that build them?

The challenge, then, is not to reject engaging AI, but to use and design it with intention: in ways that preserve human agency, sustain critical thinking, and protect the social and cognitive skills that require effort to develop.

Because the risk is not that AI is too powerful. It is that it may become so easy to use that we stop exercising the parts of ourselves that matter most.

Some of the most important Future of Work conversations are not the easiest ones.

This month’s Future of Work Club Meetup featuring our incredible club ambassador and facilitator Sean A. Fisher and special guest Myrna Rich-Ray on Workplace Sexual Harassment & Gender-Based Discrimination was a powerful reminder that workplace culture is ultimately about people, trust, dignity, and psychological safety.

Too often, organizations treat these conversations as compliance-only topics. But meaningful workplace culture requires much more than policies.

A person trying to feel safe. A person trying to feel respected. A person trying to trust that their workplace sees their humanity clearly.

That’s what stood out to me because the future of work is not just about AI. Or technology. Or productivity.

It’s also about the emotional architecture of our workplaces. The systems we normalize. The behaviors we tolerate. The courage leaders demonstrate. And the environments people experience every single day.

In a moment where organizations are moving quickly to modernize work, conversations like this remind us that progress without psychological safety is not progress at all.

The Workplace Culture Conversation We Still Need

One of the most important realities about workplace harassment and discrimination is that these issues rarely begin with policy gaps alone.

They often begin with silence.

Silence around inappropriate behavior. Silence around power dynamics. Silence around bias. Silence around retaliation fears. Silence around discomfort.

And silence has a way of becoming culture.

That’s why conversations led by experienced practitioners like Sean A. Fisher and Myrna Rich-Ray matter.

Not because organizations don’t already have policies. But because people still need language, awareness, reflection, and leadership accountability.

Too often, workplace culture conversations stay surface-level. We talk about engagement. Innovation. Belonging. Leadership.

But meaningful culture work requires us to also talk honestly about harm.

About trust. About power. About what inclusion actually feels like in lived experience.

And perhaps most importantly: About whether employees believe they can speak up without fear.

That’s the real test of culture.

Leadership Is Revealed in the Hard Conversations

One thing I’ve learned over the years is this: Healthy workplace cultures are not defined by the absence of difficult issues.

They are defined by how leaders respond when difficult issues arise.

Do leaders create safety? Do they listen without defensiveness? Do they model accountability? Do they interrupt harmful behavior early? Do employees trust the system enough to use it?

These are leadership questions. Not just HR questions.

And as workplaces continue evolving across hybrid work, digital communication, distributed teams, and generational shifts, organizations will need stronger human-centered leadership skills than ever before.

Because respect cannot simply live inside policy manuals. It has to live inside everyday interactions.

That’s why I continue to appreciate spaces like the Future of Work Community.

Not because we avoid hard conversations. But because we’re willing to have them thoughtfully.

With honesty. With humanity. With care.

The future of work conversation must include emotional safety. It must include dignity. It must include equity. And it must include leaders willing to move beyond performative culture statements toward real accountability.

Because innovation means very little if people do not feel safe enough to fully participate.

And perhaps that’s one of the most important leadership truths of all.

Always human in the lead.
Always grounded in practice.

Cheering you on,
~Liza

If you’re driving 90 miles per hour and your wheels aren’t aligned, you don’t feel the danger at first. The engine hums. The speed feels efficient. You’re covering ground faster than ever.

Until the steering starts to shake.

That’s where we are with AI and that’s the real story about the Future of Work.

The Wrong Question

Everyone keeps asking: “Are we behind on AI?”
Wrong question. The better question is:

Are we stabilizing as fast as we’re accelerating?

Because AI is no longer a novelty. It’s infrastructure.

Donald H. Taylor opened our recent session with Paige Bergman by describing this year’s survey as the most significant in thirteen years, not for what changed dramatically, but for what stopped behaving predictably.

That isn’t a trend shift. It’s structural instability that forces leadership to either mature… or fracture.

The Signal Beneath the Rankings

Yes, AI topped the survey again. But the more interesting rise was “Showing Value.”

That tells me something. When a profession shifts its attention from innovation to validation, it means pressure has entered the room.

• Budget pressure.

• Credibility pressure.

• Identity pressure.

Watch the Replay

Paige Bergman, OpenSesame’s Director of Curation, grounded this tension in operational reality. As she noted during our session, acceleration is visible, but alignment is invisible work. Organizations are moving fast on tools, but far slower on the governance, expectations, and capability systems that make those tools sustainable.

In the chat, other leaders across industries echoed the same sentiment:

“We’re moving fast, but we don’t feel steady.”

That’s acceleration without stabilization.

Progress and Pressure at the Same Time

One of the most insightful tensions in the survey was this:

L&D is embedding AI into daily workflows.

And simultaneously:

• Struggling to demonstrate impact

• Facing tighter budgets

• Wrestling with role clarity

• Experiencing increased scrutiny

That’s not failure. That’s transition. But transition is chaotic.

Donald guided to George Land, in Grow or Die, described transformation as a period where old norms collapse before new ones stabilize. It feels disorienting because the old rules don’t apply, and the new ones haven’t yet solidified.

The Alignment Problem

Here’s what concerns me most.

• We are redesigning workflows.

• We are embedding automation.

• We are expanding expectations.

Paige made a point that stayed with me: stabilization is leadership work. Technology teams can deploy infrastructure quickly. But aligning managers, clarifying accountability, and building capability across functions requires intention. That gap, between deployment and alignment, is where strain begins.

And we are not aligning at the same speed.

Not governance.
Not culture.
Not leadership capability.

At high velocity, misalignment isn’t innovation. It’s risk.

Peter Drucker once wrote, “The greatest danger in times of turbulence is not the turbulence; it is to act with yesterday’s logic.”

Many organizations are adopting tomorrow’s technology while still operating inside yesterday’s models. That tension, between innovation and infrastructure, is the real readiness gap. It isn’t about whether the tools work. It’s about whether the organization does. It’s about human readiness, leadership maturity, governance clarity, and cultural alignment. When technology advances faster than operating models evolve, the gap isn’t technical, it’s structural.

Let me be clear: the survey is not a doomsday report. It’s a transition report. And transitions are where the future gets shaped. If we stabilize while we accelerate, we build trust, clarify identity, align governance, and design work intentionally. But if we accelerate without stabilization, we exhaust people, blur accountability, amplify pressure, and erode trust, not because AI is dangerous, but because misalignment is.

If You Lead Right Now, Stabilize Like This

Before you accelerate, stabilize.

• Stabilize identity: What does L&D actually own in this new operating model?
• Stabilize governance: Who decides what AI does, and who is accountable when it fails?
• Stabilize capability: What skills truly matter in a Human + AI workplace?
• Stabilize culture: How do we protect judgment, trust, and human agency?
• Stabilize expectations: What does “doing more” actually mean — and at what cost?

Then accelerate. In that order, because speed without alignment is noise, and alignment without action is stagnation.

The organizations that win this era will not simply adopt faster. They will stabilize smarter.

Acceleration without stabilization is not strategy. It’s drift. And in 2026, drift is not an option.

Onward and upward. 🚀
~ Liza

Everyone keeps asking:
“Are we behind on AI?”

Wrong question.

AI is no longer a novelty. It’s infrastructure.
And when infrastructure moves faster than organizations can stabilize around it, people feel pressure.

That pressure? That’s what the 2026 Global Sentiment Survey by Donald H. Taylor is surfacing.

Download the survey here:
https://donaldhtaylor.co.uk/research_base/global-sentiment-survey-2026/

This isn’t a panic report.
It’s a transition report.

We are accelerating.
But we are accelerating without stabilization.

We’re embedding AI into workflows.
We’re expanding expectations.
Employees are being told, “Now that you have AI, you can do more.”

Roles are being redesigned.
Layoffs are being labeled “AI.”
Governance is lagging.
Trust is lagging.
Identity is lagging.

This isn’t a technology readiness gap.

It’s a human and organizational readiness gap.

The companies that win in this era won’t just be the fastest adopters.

They’ll be the ones who:

• Accelerate performance

• Stabilize culture

• Redesign governance

• Protect trust

• Clarify identity

The real question isn’t:
“Are we behind?”

It’s:
What are we intentionally redesigning right now?

Because if you don’t design the future of work on purpose…

It will be designed for you.

See you in the future of work.
~Liza

Sometimes the most important workplace conversations are the ones that slow us down enough to actually hear each other.

There’s something deeply grounding that happens when people gather not to perform expertise, but to reflect together.

Not to debate trends.
Not to “future-proof.”
Not to impress one another with vocabulary or frameworks.

Just to think out loud about what it means to work, lead, navigate tension, and stay human in systems that often move faster than people can process.

That was the feeling underneath this month’s Future of Work Monthly Club Meetup with Sean A. Fisher and featured guest Kelly Hams Pearson, where the conversation explored mediation, negotiation, workplace conflict, and the growing tension between technology and human understanding.

And honestly? The conversation felt less like a webinar and more like a collective exhale.

The Future of Work Isn’t Just About AI, It’s About Human Interpretation

One of the strongest moments from the discussion came when participants reflected on the limits of AI in human communication.

As the chat unfolded, someone shared:

“There’s a lot said in between what’s said.”

And immediately, the room felt that.

Because that’s the work, isn’t it?

Not simply hearing words.
But understanding pauses.
Tone.
Fear.
Defensiveness.
Uncertainty.
Context.
Human nuance.

Another attendee added:

“I don’t think AI is good at that.”

That tension became one of the most important undercurrents of the session:
As organizations race toward automation and AI-first strategies, many employees are quietly asking a different question:

Who helps hold the human complexity?

Kelly Hams Pearson brought a grounded and deeply practical perspective to mediation and conflict resolution — not as “soft skills,” but as essential infrastructure for modern workplaces.

Not every conflict needs escalation.
Not every misunderstanding needs punishment.
Sometimes people need structured space to feel heard before collaboration becomes possible again.

That landed deeply with attendees.

Conflict Resolution Is Becoming a Leadership Skill, Not Just an HR Function

One insight that kept resurfacing throughout the conversation was the idea that organizations need cultures of conflict resolution, not just policies for conflict management.

I reflected in the chat:

“I like how you said that about a culture of conflict resolution - like a neutral party that is not HR to support employee concerns…”

That distinction matters.

Employees are increasingly looking for psychologically safe pathways to navigate tension without immediately triggering formal systems, defensiveness, or fear.

And leaders are realizing something important:
Workplace conflict is rarely just about disagreement.

It’s often about unmet expectations.
Miscommunication.
Power dynamics.
Stress.
Change fatigue.
Or people trying to navigate systems that were never designed for this level of complexity.

What stood out most was how practical the conversation remained throughout the session.
No hype.
No exaggerated promises.
No fear-based framing.

Just thoughtful reflection around what humans still uniquely bring to work:
judgment, empathy, interpretation, discernment, and relational trust.

Ironically, those may become the most valuable skills of all in an AI-enabled future.

The Real Future of Work Question

The future of work may not simply be:

“What can AI do?”

It may become:

“What should humans continue holding sacred?”

Attention.
Nuance.
Trust.
Conflict navigation.
Emotional intelligence.
Community.
Interpretation.

The things that don’t scale easily may end up being the things that matter most.

And maybe that’s why these monthly conversations continue to resonate.

They create rare space for people to pause long enough to think together — not just consume information.

That matters more than we realize.

If you missed the session, I highly recommend catching the replay and joining a future meetup. The conversations are thoughtful, practical, and refreshingly human-centered in a time when many workplace discussions feel rushed or transactional.

Always human in the lead.
Always grounded in practice.

Cheering you on,
~Liza

Her name is Catherine. She’s 47, a senior leader, respected and sharp, the person everyone turns to when things get complicated.

Lately, though, something feels different. She forgets a word mid-sentence in a meeting. She rereads emails three times before hitting send. She wakes up at 3:12 a.m. almost every night and can’t fall back asleep.

She tells herself she’s slipping. That she needs to focus. That she just needs to push harder. Her performance reviews are still strong. Her team still trusts her.

But inside? She’s questioning everything.

No one at work knows what’s happening, not because she’s hiding something, but because she doesn’t yet have language for it.

Now zoom out. Claire isn’t an outlier. She’s one of millions.

February is often about progress - performance goals, Q1 momentum, execution. But progress without inclusion isn’t progress at all.

For our second Future of Work session of the year, we tackled something workplaces have avoided for far too long. Not because it isn’t important, but because it’s been uncomfortable:

Menopause at work.

If we are serious about the future of work, we must be serious about the full human lifecycle at work.

Why This Conversation, Why Now

Over 90% of women experience perimenopause and menopause. Many do so at the peak of their careers. And yet most workplaces still lack:

• Clear policies

• Structured support

• Manager training

• Practical accommodations

The result?

• Brilliant women quietly struggling.

• High performers questioning themselves.

• Leaders leaving roles unnecessarily.

This isn’t just a health issue. It’s a leadership issue. A retention issue. A compliance issue. A culture issue. A Future of Work Issue.

The future of work cannot be built on silence.

Watch the Replay

🎙 A Conversation Grounded in Evidence, Not Assumptions

I had the privilege of co-hosting this conversation alongside:

• Amanda Sessions, Enterprise Curator of Compliance, OpenSesame

• Nick Henderson-Mayo, Head of Compliance, VinciWorks

• Naomi Grossman, Compliance Manager, VinciWorks

• Erienne Koanui, People Operations Generalist, OpenSesame

What made this session powerful wasn’t shock value. It was clarity. We explored what perimenopause actually looks like:

• Brain fog

• Anxiety

• Fatigue

• Sleep disruption

Symptoms that are often misinterpreted as disengagement, underperformance, or burnout. We discussed how many women don’t initially recognize what they’re experiencing, and how managers often miss early signs entirely. And we addressed the practical question leaders ask: What can we actually do?

🔍 Key Insights from the Session

1️⃣ This Is About Retention, Not Just Awareness

One of the most striking realities discussed:

Many women leave roles unnecessarily.

Not because they lack capability.
Not because they lack ambition.
But because the workplace lacks adjustment.

Sometimes the solution isn’t complex.

It’s flexibility.
Temperature control.
Meeting structure.
Psychological safety.
Manager awareness.

Low-cost.
Sometimes no-cost.

But high-impact.

2️⃣ Policy Without Culture Doesn’t Work

Nick and Naomi shared insight into the evolving legal and regulatory landscape — particularly in the UK, where menopause action plans are gaining traction.

But compliance alone isn’t enough.

You can write a policy.
You can add a clause.
You can update a handbook.

But if women don’t feel safe speaking up, the policy stays on paper.

Culture determines whether policy becomes practice.

3️⃣ The Manager Multiplier Effect

One of the most powerful themes:

Managers don’t need to be medical experts.

They need to be human.

When managers are trained to:

• Recognize patterns

• Listen without judgment

• Adjust without embarrassment

• Respond without minimizing

Everything changes.

This is not about “special treatment.”
It’s about equitable treatment.

The future of work demands leaders who understand that life stages impact performance — and that support fuels excellence.

4️⃣ Silence Is Expensive

Perhaps the most relatable moment of the session was this realization:

How many women have internalized symptoms as personal failure?

How many have thought:
“Why can’t I keep up like I used to?”
“Why am I forgetting things?”
“Why am I so exhausted?”

When biology is mistaken for incompetence, confidence erodes.

And when confidence erodes, talent walks out the door.

Organizations cannot afford silence — not ethically, not strategically.

🌱 What Positive Change Actually Looks Like

This session wasn’t about creating complexity.

It was about evidence-based action:

• Implementing low- or no-cost adjustments

• Building a structured Menopause Action Plan

• Understanding global regulatory movement

• Reducing litigation risk

• Creating environments where women feel safe to speak

This is how we evidence positive change.

Not through statements.
Through systems.

🔗 Continue the Conversation

• 🎥 Watch the on-demand replay

• 📚 Explore menopause and workplace culture learning resources

• 📊 Take the Future of Work Readiness Survey

✨ Final Reflection

The future of work is not just about AI. Not just about automation. Not just about productivity. It’s about designing systems that reflect real human lives. Menopause is not a niche issue. It is a workforce reality.

And if we want organizations that retain talent, build trust, and lead with intelligence, we must normalize conversations that were once whispered. Technology may define the next era of work. But courage will define the culture.

Thank you for being part of this community, and for helping us build workplaces where every stage of life is respected, supported, and valued.