It’s pretty incredible to think about how much exists now that didn’t a year ago in the AI music world. Music discovery platforms. Online communities of music-makers. Detection software. Laws and policy changes. An entire cottage industry.

You have to add Zinstrel to that list.

We celebrated a year of existence on Aug. 28 — and none of it happens without you readers, including the small but growing group who’ve become paying subscribers along the way. It means everything that you value this publication the way you do.

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I’ve had some version of this conversation with dozens of people in this space over the past year — founders, artists, editors, strangers at conferences — usually in fragments, on the fly. This is the first time I’ve sat down and told the whole thing at once.

So for this special edition of Culture, the subject isn’t a scene, a platform, or an artist. It’s Zinstrel itself. Now feels like the time for a proper introduction: who I am, how this happened, and what we’re actually trying to do here.

Musical Origins

It almost always surprises the anti-AI crowd to learn that not only am I a musician, but a classically trained one.

I entered college as a vocal performance major on a full ride to Portland State University, with dreams of becoming an opera singer. But piano proficiency was required, and I couldn’t play piano to save my life. I also wasn’t interested in teaching, so I walked away from the scholarship for my other love: writing and journalism.

The music never stopped. At the University of Oregon’s School of Journalism (Go Ducks!), I played guitar, wrote music, and sang with On The Rocks, the school’s all-male a cappella group.

After college, I started in newspapers and became the youngest Managing Editor of a newspaper in the Northwest, leading The Sandy Post outside Portland. A pro bono contributor role for a small album review site (TSRocks.com) grew into my role as Executive Editor of NewReleaseTuesday, where I interviewed countless artists, went on nationwide tours, co-founded an awards show, and hosted a daily livestream.

When that job ended, I spent the next half-decade-plus in content leadership and writing my own music — I’ve released two pop EPs and a couple singles — but missing the music industry.

Then I discovered Suno.

Finding the Gap

In early 2024, I saw on social media that people were making songs with AI through Microsoft Copilot. I made a catchy “summer song” and had to learn more.

I realized Copilot had white-labeled Suno, subscribed, and started giving new life to old lyrical projects. I can play music, sing, and develop my own ideas, but digital audio workstations aren’t intuitive for me. Suno let me channel what I already had into something audible.

As I got deeper into the ecosystem, I found others doing the same. But there was little connectivity, editorial voice, or curation. Scene reporting was sorely missing.

Household-name tech publications covered AI music, but mostly as an aside. Nobody was dedicating all of their attention to AI music news, culture, and analysis. I saw a part for me to play.

First, I needed a name. After hours brainstorming with ChatGPT, I landed on “Zinstrel” — a twist on “minstrel,” with a futuristic Z up front. I liked the idea of zinstrels as the bards and soundtrack-makers of the 21st century.

On Aug. 28, 2025, I registered zinstrel.com (and zinstral.com, since I worried people couldn’t spell it).

But what would Zinstrel actually be?

I jumped on Squarespace and Instagram and started building simple guides, quizzes, and “song obsessions.” They were great, but it felt like my NRT instincts rebooted for an AI audience. In an age where AI could provide much of that information with a simple prompt, this had to be bigger than a website.

Finding the Voice

Substack was calling. I saw it as a platform for “real” journalism — a simple distribution method for writers. Plenty of well-respected journalists who had gone independent were using it. It felt like a beautiful marriage of the early 2000s blogosphere and Twitter before it went bonkers.

My first commentary on breaking news came once Udio inked a settlement deal with Universal Music Group. Days later, at the Music Tectonics Conference in Santa Monica, I watched discussions about AI artists and heard UMG representatives introduce “Active Listening” and superfan remix tools as part of the label-approved future of AI music.

I left Tectonics with renewed purpose that led me to start our three-times-a-week newsletter on Black Friday 2025. The initial strategy was to shift my simply sourced news briefs from Zinstrel.com to Substack.

Then I shared the newsletter with one thoughtful person on LinkedIn and got some scathing — in a good way — feedback: the world wasn’t looking for another AI-powered headline curator. It needed a unique voice and perspective. I wasn’t giving it.

That changed everything.

I unveiled three different weekly formats to keep myself focused — which you now know as Signals, Culture, and Frame. I did hours of my own research with each issue. I wrote my own words, only using AI to help with organization, mechanics, and flow.

100 Issues Later

Fast forward, and in August I hit my 100th issue. We’re also closing in on 1,000 Substack subscribers.

I took a second to look up and actually dig into who was reading Zinstrel. I knew it was a quality list of professionals, but I hadn’t realized how concentrated it had become.

Roughly one in eight subscribers has an email address tied to a music, audio, or music-tech business. There are readers at Universal Music Group, Deezer, Ministry of Sound, Audible Magic, LALAL.AI, Staccato AI, and Soundverse, alongside people from music law, independent labels and studios, and other corners of the industry. Readership includes founders and product leaders building AI music tools, academics studying the space, journalists, producers, working artists, and hobbyists and leaders in the various AI music communities.

And it’s not just concentrated professionally; it’s increasingly global. Zinstrel has readers in more than 40 countries, from the U.S., UK, France, Germany, and Australia to South Africa, Brazil, Morocco, Hong Kong, and Thailand. What surprised me most was realizing that this new publication had managed to quickly bring together people from almost every side of the same conversation: people building the technology, people working inside the traditional music business, people studying and covering what it’s doing, and people actually making music with it.

In a recent interview, I told Shawn Singh, “I’m very proud of the readership we have developed, full of leaders in tech, the music industry, and the creator community. I’m humbled that Zinstrel has become a must-read for them.”

15 Stories That Defined Year One

Earlier this year in Indiana, I heard a professor say that in the world of AI, 90 days is the equivalent of a year of development.

So at this point, I’ve been active for “four years” in AI time, and it has felt like it.

The pace of this industry is breakneck, and I love it, because there’s plenty of opportunity to innovate, break news, and redefine how the space gets covered.

If you’re newer to Zinstrel, these are 15 of my favorite stories — and probably the best way to understand the mix of news, culture, and analysis I’ve been trying to build:

1. The ‘Slop’ Problem Isn’t AI — It’s Creative Shortcuts (#015, Jan. 26)

2. AI Artists Are Coming to the Stage. Don’t Be Scared (#021, Feb. 9)

3. AI Music Gives People with Disabilities a Chance to Create (#022, Feb. 13)

4. The AI Concept Album Heaven.exe Was Built, Not Prompted (#046, April 8)

5. Prepare Now for the Post-Suno Era (#047, April 10)

6. The Music Industry Is Missing Another Underground Movement (#50, April 17)

7. SSC: The Song Contest That is Becoming AI Music’s Global Stage (#055, April 29)

8. Here’s the Map of AI Music Culture (#058, May 6)

9. Conflicting Origin Stories Surround No. 1 AI Song (#066, May 25)

10. MP3.com Has a Warning for Suno (#071, June 5)

11. This Might Be AI Music’s First Real-World Meetup (#076, June 17)

12. Five Things AI Creators Wish You Knew (#079, June 24)

13. Is This the World’s First Mainstream AI Music Hit? (#080, June 26)

14. Zinstrel #100: The 100 Names You Need to Know (#100, Aug. 12)

15. Global Cultures Are Expanding AI Music (#106, Aug. 26)

Quick, important note: some of these are paywalled. Anything older than 90 days gets paywalled, reserved for Zinstrel’s paying subscribers. Currently, I have a couple-dozen fantastic paid subscribers, and would invite you to join them.

While this has been enjoyable, it’s not free to do, and it takes away from time for the actual money-making I have to do. If the content is valuable to you, I’d invite you to subscribe. Since I give you roughly 12 issues every month, the $8/month subscriber rate means each well-researched, agonized-over issue would cost you less than $1.

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What Year Two Is For

Year One was largely about proving there was actually a story here. I don’t think I have to prove that anymore.

AI music now has a cottage industry, communities, conferences, lawsuits, licensing deals, discovery platforms, charts, festivals, artists, haters, and an increasingly complicated relationship with the traditional music industry.

I’ve also learned that the threat AI music poses to the mainstream music world is overblown, and that most creators really just want to express themselves and connect with others (not make money). This is still a deeply human industry, full of stories and talent — just expressed through different skill sets.

The job of making sense of this industry has never been bigger.

Looking forward, as we’re about to hit 1,000 subscribers, I’m looking to bring on more writers and introduce more features. Look out for more experiments that map and celebrate the space, like Culture Vision, a collaboration with the AI Music Embassy, campaigns with popular and up-and-coming AI tools, and more artist exposure.

I also want Zinstrel to keep getting better at identifying where the real movement is: who’s pushing the medium forward, which communities matter, what deserves attention, and what is just noise.

I want to give serious creators and new platforms exposure — because this space is much bigger than Suno, despite it owning the conversation. I want people inside the traditional music industry to better understand what’s happening outside their normal field of view, and people inside AI music communities to better understand why that industry is reacting the way it is.

Most of all, I want to keep mapping this culture while the map is still being drawn.

The Ask

But to that end, a peek behind the curtain.

Despite bizarre claims and conspiracy theories thrown at me earlier this year, I’m not paid by Suno. I’m on nobody’s payroll; this is my own labor of love.

But keeping pace with this space, while building some of the projects I have in mind for Year Two, will take more support.

If Zinstrel has become part of your regular reading, I’d invite you to support it at $8/month. And if paying isn’t in the cards, if there’s something you like, please send it to someone or repost it on LinkedIn, Instagram, or Substack. Or grab some Zinstrel merch. That supports this, too.

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A year ago, I wasn’t sure there would be enough happening in AI music to sustain an entire publication. More than 100 issues later, my bigger challenge is keeping up.

Thank you to everyone who has trusted me with your time, attention, stories, disagreements, tips, and information this year.

Here’s to the year ahead.

🎧 Song of the Day: “Barcelona És Gaudí” by Cienpeligros

“Barcelona És Gaudí” began as a soundtrack for a creative shoot by wedding-planning school Escuela Imagina, blending Catalan rumba with classical instrumentation to capture the color, architecture, and energy of Barcelona. After winning Spain’s qualifying round and earning the jury’s highest score among more than 400 entries, the song advanced to a 63-song final — and won the entire Fairovision competition, becoming the overall champion of what organizers describe as the first international contest for AI-produced songs.

💬 Last Word

“Nothing about the AI future is already decided. We get to participate in shaping it too.”

— The Human Playbook on Substack

Zinstrel: AI Music News & Discovery is a 3x/week publication covering the tools, culture, and power shifts shaping AI music. Subscribe to stay in the loop — free or paid.

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MORE ZINSTREL:
Zinstrel.com | @zinstrel_ai on IG | AI Underground on Discord

Written by Marcus Lawrence, courtesy of composition platform Versey.ai.

Special thanks to our paid subscribers: Blue Hermit, C.Y. Lee, Charles S., Daniel Drolet, Daniel Lares, Daryl Dekking, Dexter Garcia, Drew Thurlow, Jacci Cenci-McGrody, Lenny Skolnik, Lynn Clapp, Marc Wolinsky, Matthew Marturano, Matti Kuha, Mete Dibi, Sheila Spence, Steve Clapp, Steve Grossman, and Tim Burley.

On Sept. 3, Suno's new terms of service will go live, and as part of that, user downloads will be limited. Free accounts will only get seven lifetime downloads, Pro will get 20 a month, and Premier will get 60 — and the online communities made up of Suno creators are scrambling to adapt before the deadline hits.

Many of the community's radio stations, livestream listening parties, and song contests were built around playing tracks pulled straight from Suno links — infrastructure that now has to be rebuilt around officially downloaded files (while keeping those masters private). The cap doesn’t just limit how many songs a user can save; under Suno’s new terms, officially downloaded files are also what unlock off-platform commercial use for eligible paid-plan songs.

The changes were a topic of concern at Tuesday’s AI Music Embassy meeting — a coalition of leaders from major AI music communities, mostly Discord servers, representing an estimated 20,000 creators. No unified standard has emerged, though every group is weighing how to adjust. The underlying question: Suno links grant access, not portability. As Zinstrel has reported, for eligible paid-plan songs, only the Download button confers commercial rights surviving cancellations and downgrades — forcing groups to decide how to handle Suno songs before time runs out.

AIPlay, the leading infrastructure for Suno-link listening parties, took a lighter touch: links still play through Suno’s embed, but rhythm games, radio rotation, karaoke, and the store now require an uploaded MP3. New rights-declaration prompts — songwriting registration, paid-plan status, remix status — accompany every submission.

AI:Underground says it saw this coming: co-founder Daniel “Ghost Ryder” Lares says the platform never relied on embedded Suno audio and always required creator-submitted MP3s — so nothing changes Sept. 3.

Bancamp’s core DSP was already upload-based; its one Suno-dependent listening party, theNOISEpocket, will keep using Suno’s player rather than build new extraction tooling.

Soné.fm, an AI radio and streaming platform, says Suno has begun blocking external playback — encryption gating, per founder Mims Talsi — pushing artists toward AI-native platforms, given more than 80% of tracks aired on Soné originate from Suno.

Discord server HellcatNZ had to retool its King of the Hill contest and 24/7 radio: instead of pulling songs from Suno links, the bot now requires artists to upload their officially downloaded MP3s, so no one can grab someone else’s master from a public channel. The station becomes a rotating “league” — each week’s top three King of the Hill finishers who opt in join the 24/7 rotation, bumping the bottom three out.

Five different fixes with one shared calculation: whether a link is still enough, or whether only the officially downloaded file counts from here.

SSC Moves Its Next Challenge to Vibya With Sponsored Prizes

The Social Song Contest (SSC) is moving its next creator challenge to Vibya, the social music discovery platform that grew from the same community. The Blow Us Away Challenge asks creators to make a song led by brass or woodwinds, with submissions Sept. 7–13 followed by blind, randomized voting on Vibya. It’s also SSC’s first challenge with sponsored prizes: Neural Frames, Google Flow Music and Eleven Music are contributing rewards for top entries and category winners. The live finale and results are scheduled for Oct. 2.

Bancamp Launches 3D Virtual AI Music Festival

AI music discovery platform Bancamp will host BanFest Sept. 4–6, a three-day virtual festival built inside a custom interactive 3D website. The event combines AI-generated music, video art and community networking, with visitors navigating the grounds using avatars, chatting live and moving between multimedia stages. BanFest will also debut an AI-Live Album featuring 20 creators and 40 songs, with each artist contributing one original and one cover of another participant selected by a wheel of fortune. The grounds will include community tents from groups including StorytellerZ, Fresh Friday Festival, Souxes, and Zinstrel, an Artist Alley, access to Bancamp’s music catalog and creator merch stores, plus achievements and reinterpreted arcade games scattered throughout the environment. Some participating artists have also created music videos that will screen on the festival’s main stage and appear in a companion YouTube playlist.

ElevenMusic Adds Composer and Conversational Co-Writer Muse

ElevenLabs has added two new creation tools to ElevenMusic: Composer, which lets users edit individual song sections without regenerating the full track, and Muse, a conversational co-writer that handles revisions through plain-language instructions. Creators can change lyrics, tempo, key, instrumentation, structure or specific passages, compare alternate takes, and move between manual editing and AI-guided changes at any time. Together, the tools push ElevenMusic toward a more iterative production workflow where users can shape songs section by section instead of relying on one-shot generation.

Flow Music Expands Lyria Across Covers and Realtime Creation

Flow Music has expanded its Lyria-powered creation tools across both remixing and realtime generation. Its Covers feature now uses Lyria 3.5, allowing the Producer agent to reinterpret songs creators have already made, while Lyria RealTime is now integrated into Spaces, where changes to genre, instrumentation and other musical elements can be heard within seconds. Together, the releases move Flow Music further away from one-shot generation and toward an environment where creators can continuously reshape, remix and explore a track as part of an ongoing, interactive production process.

Sony and Warner Publishers Sue Anthropic for Billions

Sony Music Publishing and Warner Chappell Music have sued Anthropic, accusing the company of illegally copying tens of thousands of copyrighted compositions to train its Claude models. Filed Aug. 28 in federal court in California, the complaint alleges Anthropic obtained works through torrenting, lyric scraping and book scanning, including songs such as “Eye of the Tiger” and “All I Want for Christmas Is You.” The publishers are seeking a jury trial and up to $150,000 per willfully infringed work, potentially putting damages in the billions.

UMG and Sony Add YouTube Stream-Ripping Claim to Suno Lawsuit

Universal Music Group and Sony Music Entertainment have expanded their lawsuit against Suno, alleging it used YT-DL and YT-DLP to download copyrighted recordings from YouTube and bypass the platform’s “rolling cipher” while collecting training data. Judge F. Dennis Saylor IV allowed the DMCA anti-circumvention claim to proceed, although he has not ruled that Suno actually violated the law. The allegation adds a second question to the AI training fight: not only whether using copyrighted music is fair use, but whether obtaining that training material was itself unlawful.

All Three Major Labels Invest in Stability AI

Universal Music Group, Sony Music Group and Warner Music Group have all taken equity stakes in Stability AI through its new $76 million Series B funding round, alongside investors including Electronic Arts and AMD Ventures. Universal and Warner were already strategic Stability partners, while the company’s Stable Audio 3.0 was trained entirely on licensed music data; Sony’s investment now puts all three majors behind the same generative music developer. It’s another indication that major labels aren’t rejecting generative AI itself — they’re increasingly backing versions built around licensing, rights-holder partnerships and professional creative workflows.

HumanStandard Brings Ethical AI Music Challenge to Philadelphia Hackathon

AI music detection company HumanStandard is partnering with Coffee & Code Philadelphia on an “ethical AI music challenge” during its Sept. 20 AI Agent Hackathon at the Pennovation Center. Participants will be able to use HumanStandard’s AI music detection technology to build projects around responsible AI, with an intentionally broad brief aimed at encouraging new ideas rather than simply automating existing creative work. Founder Rasha Rahman says the challenge is particularly aimed at students and early-career developers. HumanStandard is also seeking sponsors to contribute additional prizes or API credits for participants.

Controlla Voice Opens More Free Songwriting Sessions for LA Artists

Controlla Voice is opening another round of free songwriting and production sessions at its Santa Monica studio, where selected artists can develop a track with producer Jeff Ng and have the process featured through Controlla’s YouTube content. Ng, a Controlla executive whose credits include work for Disney, Universal and Netflix, will produce the sessions at no cost. The program extends Controlla’s creator-led strategy of putting musicians, production workflows and content around its AI tools — using a physical studio and working artists as the company’s bridge into broader music-making culture.

🎧 Song of the Day: “Mine Again” by Schwarzlochmusik

“Mine Again” by Schwarzlochmusik is the emotional, symphonic pop song that won the third edition of MobVision Song Contest at its recent Grand Final, representing Berlin, Germany. It topped a field that began with 132 submissions and was narrowed to 28 finalists through qualifiers and semifinals.

💬 Last Word

“Synthetic music can be produced and distributed at a speed that human creators will never match, but upload volume is not the same as cultural impact.”

— Bas Grasmayer, Growth Strategy at Vandall, via HypeBot

MORE ZINSTREL:
Zinstrel.com | @zinstrel_ai on IG | AI Underground on Discord
Copyright 2026 Zinstrel, LLC - All rights reserved

Written by Marcus Lawrence, courtesy of composition platform Versey.ai
Special thanks to our paid subscribers: Blue Hermit, C.Y. Lee, Charles S., Daniel Drolet, Daniel Lares, Daryl Dekking, Dexter Garcia, Drew Thurlow, Jacci Cenci-McGrody, Lenny Skolnik, Lynn Clapp, Marc Wolinsky, Matthew Marturano, Matti Kuha, Mete Dibi, Sheila Spence, Steve Clapp, Steve Grossman, and Tim Burley.

It seems we’ve forgotten why music charts exist in the first place.

They didn’t start as pop culture bragging rights; they started as a business tool. Billboard’s first sales chart, in 1940, let a label in New York know a song was actually moving units in Memphis instead of relying on a retailer’s gut feel.

Britain’s first official singles chart, published by New Musical Express (NME) in 1952, emerged to settle a related problem: too many trade papers running contradictory rankings, with no way to say who actually had the number-one song. The Billboard Hot 100 appeared six years later.

Consolidating around one trusted source is what made a chart position mean something at all. The whole point, from the start, was to report as accurately as the data allowed what people were actually buying and listening to. Not to referee how a song got made.

It seems in the AI era, the powers that be are forgetting that.

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The Year the Rules Changed

In 2026, anti-AI sentiment stopped being a comment-section complaint and started rewriting how charts actually operate.

Sweden went first in January, excluding Jacub’s “Jag vet, du är inte min” from its official singles chart, Sverigetopplistan, because of its use of AI.

By summer, what looked like a one-country reaction had hardened into an international policy movement. Music-industry groups introduced a shared AI-labeling standard in July. Major labels then proposed chart-eligibility principles built around whether a recording was “substantially human made.” The International Federation of the Phonographic Industry (IFPI) rolled those principles across its chart network the next day. Germany adopted them. Australia followed with its even stricter rules in August.

All of those moves circle the same underlying question: is this song human enough to count?

That’s a legitimate question for an awards body, a copyright office, or a licensing system.

It’s the wrong question for a chart.

Charts do have rules. They have to. They decide what constitutes a sale, which streams count, how formats are weighted, and whether manipulation invalidates the data. But those rules exist to make the measurement more accurate.

“Substantially human made” does something different. It makes a judgment about the thing being measured.

When Auto-Tune became inescapable after “Believe,” nobody proposed an asterisk next to Cher’s No. 1 chart position. When sampling turned hip-hop into a genre built partly out of other people’s recordings, the fight happened in copyright court, not on the Hot 100.

If “worthiness” were part of the metrics, a pitched-up, duck-voiced cartoon character over a generic disco beat would have never seen the No. 1 spot for one week back in 1976.

Charts should have rigorous standards. The question is what those standards are protecting: the integrity of the measurement, or somebody’s idea of creative legitimacy.

The moment a chart starts adjudicating the composition of a song instead of whether it was heard, it stops measuring culture and starts editorializing it. And is that really its job?

Two charts, two AI reveals, two very different responses.

Jacub’s “Jag vet, du är inte min” topped Spotify’s Swedish chart and passed six million streams before IFPI Sweden ruled it ineligible for Sverigetopplistan. But the streams didn’t stop — listeners kept playing it; the official chart simply refused to count them.(As of Aug. 25, it’s still No. 69 on the SIQA AI Song Charts.)

Fenix Flexin’s “RUBBERZ” took the opposite path. After months of denial, a Zinstrel report, and a viral takedown video, he admitted using AI too. Billboard left the song alone. Eleven weeks into its Hot 100 run, after peaking at No. 58, it’s still there — climbing back to No. 88 this week after dipping to No. 90 the week before.

While Sweden’s chart erased the data, Billboard kept counting. Both songs kept their audience either way.

On July 10, IFPI joined RIAA, the Grammys, SAG-AFTRA, and several other bodies in a voluntary labeling standard distinguishing “AI-Generated” from “AI-Assisted” recordings. That was a transparency initiative.

The chart rules came later. On July 29, Sony, Universal, Warner and other music companies outlined principles for AI-related chart eligibility. IFPI rolled them out across its international chart network on July 30: an AI-involved track must use an authorized and lawful service, be “substantially human made,” avoid manipulation concerns, comply with copyright and personality-rights law, stay within the AI tool’s own terms, and be appropriately disclosed.

Fail one condition, and it’s out.

Those principles now extend across IFPI-managed charts in Latin America, the Middle East, Africa and Southeast Asia, while national chart organizations including Sweden and Germany are adopting the framework.

Australia’s ARIA made the line especially concrete this week. A track with an AI-generated lead vocal or key instrumental performance is classified as “AI-Generated” and cannot chart. AI mastering, stem separation, reverb, drum machines and some secondary generative elements remain eligible.

The most recent country to take action is Finland, whose IFPI-affiliated chart — Suomen Virallinen Lista — moved to exclude fully AI-generated recordings. Its revised rules went a step further than Australia, requiring that any AI tool used in an otherwise human-made track be properly licensed, with songs found AI-generated after charting removed retroactively. That means Suno and Udio songs are automatically out.

So far, the U.S. appears to be holding out. Major labels have proposed the same “substantially human made” bar for Billboard’s charts. Billboard hasn’t adopted it. AI-generated music can still chart in America — and Billboard’s stated response, at least for now, is identification rather than exclusion.

Two Tags, One Gate, Three Tiers

It’s worth separating what IFPI, Luminate, and the aforementioned Sonic Intelligence Academy (SIQA) actually do, because none of them are solving the same problem.

IFPI’s labeling standard sorts tracks into two categories: “AI-Generated” for recordings where generative AI produced all or the primary portion of the creative elements, and “AI-Assisted” for substantially human-made recordings with some generative elements.

Its chart framework then adds a binary gate: a track either clears the eligibility conditions or it doesn’t. In practice, an “AI-Generated” track can’t clear the “substantially human made” bar.

Luminate’s system, the one Billboard is leaning on, skips the gate. Its single “AI Generated” tag is based on proprietary detection plus self-reported data, with a dispute process for false positives. Nothing about the tag removes a song. CEO Rob Jonas has called it “a starting point,” leaving open whether Billboard eventually pairs it with an exclusion rule.

SIQA — which debuted the first AI music charts earlier this year — goes further with its labeling, separating tracks into:

• “AI-Assisted” (a human handles at least one core creative role while AI fills in the rest)

• “Human + AI Hybrid” (the artist clones their own voice with AI, everything else can be human or machine-made), and

• “Fully AI-Generated” (melody, lyrics, production, and arrangement all machine-made, with a human only prompting and selecting).

Unlike Luminate, none of those classifications run through a detector. Artists voluntarily disclose their process at submission, and SIQA verifies it through human review. SIQA has said it has “no interest in algorithmic accusation.”

But three tiers is still an approximation. Only 19% of tracks in SIQA’s first quarter of data were fully machine-generated — the dominant mode is augmentation, not automation. Among the same creators, 66% used AI on vocals, 64% on instrumental production, 40% on mixing and mastering, 20% for songwriting assistance, and 15% for sound design. Those figures overlap because creators combine several uses at once.

AI’s influence hits a dozen points on a spectrum, and every one of them is a place a mainstream, fully human-credited artist could quietly cross without anyone ever calling the record “AI music.”

AI-assisted mixing and mastering is already ordinary studio practice; AI-assisted vocal tuning isn’t far behind. IFPI’s two labels and Luminate’s one both require somebody to decide where “human” ends and “AI” begins.

There isn’t a naturally occurring boundary waiting to be discovered. Every system is making a policy choice about where to put one.

Jacub’s own song is the proof. IFPI Sweden ruled “Jag vet, du är inte min” ineligible for its charts as mainly AI-generated. SIQA classified the same track as “AI-Assisted” — a category that would not, by itself, make the song ineligible under IFPI’s standards.

The same song, the same underlying facts, two opposing verdicts. That’s what happens whenever a chart has to become an expert about authorship instead of an expert about who’s listening.

The Better Question

IFPI is right to ask whether a recording is lawful, whether its streams were manipulated, whether someone’s voice or identity was used without authorization, and whether the tools behind it were properly licensed.

Those questions protect the integrity of the market. The problem is the additional question: was it human enough?

Bot streams can corrupt a chart. Laundered royalties can corrupt a chart. Fraudulent metadata can corrupt a chart. Unauthorized impersonation can create a legitimate eligibility problem.

Simply using AI doesn’t automatically corrupt the count.

SIQA’s parallel AI Music Top 100 points toward a better line. Its eligibility rules focus on conduct rather than origin: no cloned voices, no manipulated engagement, no fraudulent metadata. A track fails because something about its participation is dishonest, not because a machine touched it. That’s the right line to police.

A chart’s job has never been to decide what deserves to exist. It’s to report, as accurately as the data allows, what people are actually listening to. The moment a chart starts asking whether a song deserves its place instead of whether people are choosing it, it stops being a chart. It becomes an opinion.

And an industry that spent a century building trust in its numbers by making those numbers useful is now in danger of making them conditional on a creative purity test that the technology itself is already dissolving.

Keep drawing lines that don’t hold, and the chart won’t just be incorrect. It’ll be irrelevant.

Disclosure: Editor Marcus Lawrence is a member of the SIQA Creative Advisory Council.

🆕 New AI Music Releases

Albums & EPs

• Frank Dezbal – Transcendence (Rock / Alternative)

• Neon Cathedral Music – Origami Love Machine, Pt. 2 (Rock / Alternative)

• WINTHER + DEZBAL – The Seven Veils of Illusion (Rock / Alternative)

Singles

• Delco Dude – “Save the Princess” Single (Pop)

• Frank Dezbal – “Love” Single (Rock / Alternative)

• Garbage Garden – “Fake” Single (Rock / Alternative)

• Shindig Productions – “Chronicle Boy” Single (Pop)

• Stereo Royale – “Rich Bitch” Single (Pop)

Music Videos

• Solène – “Praya” Music Video (Electronic / Dance)

🎧 Song of the Day: “If We” by Antonin Herbeck feat. Julia Ross

This emotional power pop song, which is No. 70 on the SIQA Top AI Songs Chart, would find a welcome home soundtracking a melodramatic rom-com movie scene.

💬 Last Word

“Despite the onslaught of bad press, there are growing signs of two things. First, listeners enjoy [AI music]. Second, the music industry has no incentive to stop listeners from enjoying it.”

— Author Chris Dalla Riva, via Substack

MORE ZINSTREL:
Zinstrel.com | @zinstrel_ai on Instagram | AI Underground on Discord | r/Zinstrel

Zinstrel #106: Global Cultures Are Expanding AI Music
Zinstrel #105: AI Labeling is Everywhere Now
Copyright 2025-2026 Zinstrel, LLC - All rights reserved

Written by Marcus Lawrence, courtesy of composition platform Versey.ai
Special thanks to our paid subscribers: Blue Hermit, C.Y. Lee, Charles S, Daniel Drolet, Daniel Lares, Daryl Dekking, Dexter Garcia, Drew Thurlow, Jacci Cenci-McGrody, Lenny Skolnik, Lynn Clapp, Marc Wolinsky, Matthew Marturano, Matti Kuha, Mete Dibi, Sheila Spence, Steve Clapp, Steve Grossman, and Tim Burley.

In July 2024, Philip Olajide-Philips needed a song in Yoruba. He called around to studios in Lagos, and the quotes came back at $300 to $400.

“That was just too much money,” he remembers thinking. “I didn’t have it.”

Olajide-Philips isn’t a stranger to music. He plays piano, drums, and guitar, sings, leads a choir, and has released two albums of his own. He’s also a software developer who studied AI at IBM back in 2019.

So instead of finding a way to pay the studio bill, he went looking for a way around it.

That was when he discovered, for the first time, AI tools that claimed to generate entire songs. Although the promise sounded almost perfectly suited to his problem, the results were disappointing.

“The most striking thing was that all these tools were built for the Western world, and Africa was actually omitted,” he told Zinstrel. “I put in African lyrics like Yoruba, and the white man was singing it very funny.”

The models could process the Yoruba lyrics. They couldn’t sing them like Yoruba.

To Olajide-Philips, it sounded less like a native speaker than the way a tourist reads a phrasebook aloud. That was difficult to dismiss as some obscure edge case. Yoruba is spoken by tens of millions of people worldwide.

And the problem didn’t stop with pronunciation. He found the instrumentation and musical vocabulary behind authentically African sounds lacking, too.

“How could they have done this?” he remembers asking. “Africa is large. Is it that they just want to leave us behind?”

That question is where KorinAI began.

It’s also a question now surfacing independently across raga, maqam, Amapiano, Latin music, and other traditions that don’t fit neatly inside the musical assumptions of the first generation of generative AI.

From frustration to a founder

Olajide-Philips figured he already had two pieces of what he needed: a background in software and enough musical experience to understand what the models were getting wrong. So he spent the next six months studying AI music generation.

Then, during a trip to Australia in December 2024, he entered a generative AI hackathon — a fast-paced competition where participants build applications around a provided technology stack. (We profiled one such hackathon recently.) His team placed third in an event he said drew roughly 4,000 participants.

The prototype they built together became the beginning of his African music generator.

Olajide-Philips kept working on it over the next eight months until he had a minimum viable product. He called it Korin, from the Yoruba word for “sing.”

But KorinAI isn’t attempting to build a frontier music model from scratch. That would require enormous amounts of computing power, data, and capital the startup doesn’t have.

Instead, the company builds on open-source models and adapts them for African languages and sounds using music obtained from partners, producers, artists, and copyright-cleared sources.

“We tune the model to what we are doing in Africa,” Olajide-Philips said.

Yoruba, Igbo, and Nigerian Pidgin are live today, with additional African languages planned as resources allow.

KorinAI’s goal is to make the underlying system better understand the language, vocals, rhythms, and musical characteristics it is being asked to reproduce, rather than simply putting African genre names in a menu of options within a general-purpose model.

The night the room found out

One of Olajide-Philips’ favorite demonstrations of KorinAI didn’t happen in a lab, but at a bustling conference in Abuja.

KorinAI built the music for the event, creating an entire 30-song playlist that ran throughout the day. By Olajide-Philips’ account, nobody in the room appeared to notice anything unusual about it until the emcee stopped the event.

“’I’d like to bust your bubble,’” Olajide-Philips recalled the emcee telling the audience. “’All the songs we’ve been listening to were all generated by AI.’”

The reaction changed immediately. They were shocked.

“They all came to me asking, ‘How did you do that?’”

For KorinAI, that experiment hinted at something beyond individual creators making songs.

Nigeria already requires paid licenses for the public performance of copyrighted music, and the Nigerian Copyright Commission has recently put more pressure on DJs and event managers to comply. In June 2025, the commission warned that DJs playing music publicly without authorization could face prosecution under the country’s 2022 Copyright Act.

Olajide-Philips sees an opening there.

Rather than businesses relying entirely on conventionally licensed catalogs, KorinAI says it can provide copyright-compliant songs. Those songs are available one at a time now, but the platform could eventually offer businesses an entire AI-generated catalog whose usage rights are cleared through the platform itself. In his vision, businesses get another source of music while creators participating in the KorinAI ecosystem can be compensated when that music is licensed.

“So now it has given us a sort of revenue for us,” he said. And for the artists.

It’s still an emerging business model. But it turns the thing that originally made KorinAI attractive — cheaper access to music creation — into a possible market on the other end as well.

What’s still missing, and what it would take

KorinAI now has more than 2,000 users, according to Olajide-Philips, and growth so far has been largely organic.

The platform operates on a freemium model, with new users able to generate two free songs. Olajide-Philips has much larger ambitions for its reach, but says the biggest challenge isn’t getting people to sign up or be excited about the tool. Unsurprisingly, it’s money.

“Funding has been our challenge, which is slowing down our growth,” he told Zinstrel.

That’s ratcheting up the pressure, because the roadmap is getting more ambitious.

The team is currently developing Korin 2.0, which Olajide-Philips says will allow users to upload their own voice and use it in a generated song. Direct distribution relationships with platforms like Spotify and Apple Music remain another short-term goal, so users can upload directly to those platforms from KorinAI.

The nine-person operation includes other technologists with musical backgrounds, including co-founder Solomon Ogunbowale, who left Goldman Sachs to work as KorinAI’s backend and AI engineer. Together, they’re taking the pressure in stride, and continue to see positive momentum.

The platform’s biggest outside validation arrived when KorinAI was named a Global Winner in the Culture & Heritage category at the 2025 World Summit Awards, an international digital-innovation program operating in the context of the UN World Summit on the Information Society. As one of the winning projects, KorinAI presented to an international audience at the WSA Global Congress in Vienna in May.

The recognition was notable, because KorinAI’s win had nothing to do with being able to generate just another AI song.

It won for its contribution to culture and heritage.

For Olajide-Philips, that reflects the reason he built the platform in the first place.

“An average up-and-coming artist in Africa doesn’t have the money to book a recording studio or session musicians,” he said. “Some of them have real talent, but they need to at least get their demo out there.”

He remembers one musician who had been sitting on lyrics for years finally hearing them turned into a song.

“I just cannot believe that my song I wrote many years ago is now live,” the musician told him.

The studio bill that Olajide-Philips couldn’t afford had become someone else’s way around the same problem.

“As AI becomes mainstream, Africa must not be left behind,” he said. “I am building KorinAI to ensure African culture is represented, preserved, and amplified.”

It isn’t just Yoruba

The interesting thing is that Olajide-Philips arrived at that argument at roughly the same moment builders elsewhere began reaching versions of it themselves.

In India, Debjit Mitra’s RaagaPay is tackling a different failure in the same underlying system.

Indian classical music doesn’t map cleanly onto the 12-tone equal-tempered framework that dominates Western music technology. RaagaPay is building a rights-cleared training corpus around concepts such as shruti, raga, tala, ornamentation, and musical lineage, with dozens of metadata points attached to each performance.

Its pitch to AI developers is essentially that calling something “Indian classical” isn’t enough. The model has to understand the musical system underneath it.

Musica AI, led by Yoan Valiente, is approaching Latin music from a similar direction, treating cumbia, bachata, son cubano, and other traditions as distinct musical systems rather than collapsing them into a generic “Latin” category.

And in Africa, KorinAI is just the beginning of what’s emerging. In South Africa, Gift Lubele’s Auraa started with what it describes as the region’s first fully AI-generated Amapiano album before expanding into Afrobeats and Highlife, building a catalog of roughly 1,500 tracks and more than 700,000 Spotify streams while picking up a Huawei Grand Innovation Award. AfroNova, operating out of Lagos and Johannesburg, is pursuing similar territory.

And at Wits University, the AI & Africa Music project is taking a less commercial route, with five artist-engineer teams developing culturally rooted AI projects around preservation, archives, education, performance, and community-controlled data. One of them, the Bɛ̀bɛ̀i Engine, was co-created with Cameroon’s Baka community around polyphonic singing, water drumming, and yodeling traditions.

And this is only the beginning: in the Gulf, Riyadh-founded rhythmi and NabadAi are building maqam-aware, Arabic-dialect-fluent systems, while in Jamaica, OpenJM is rolling out culturally grounded music generation into a broader platform built around data sovereignty.

Across the world, the products are different, the business models are different, and the cultures are different. But they’re increasingly trying to solve versions of the same problem: making sure AI understands their musical traditions as systems in their own right, rather than approximations of somebody else’s.

What it all comes back to

None of these projects is really making the argument that every musical culture needs its own isolated AI. Instead, each makes a case against treating one musical system as universal.

Train a model to understand one tradition in fine detail and leave everything else to approximation, and the result isn’t neutral. One becomes the baseline. Everything else becomes a variation on it.

That’s what builders like KorinAI, RaagaPay, Musica AI, Auraa, and the Wits teams are trying to change. AI can already make something that sounds African, Indian, Latin, or Arabic. The harder task is teaching it to understand raga, Amapiano, Yoruba delivery, maqam, and other traditions as musical systems with rules of their own — rather than deviations from whatever the model learned to call normal.

For the builders behind these platforms, that is bigger than just expanding what AI music can do. It’s carrying their musical heritage into AI on its own terms.

💿 SIQA Top AI Songs of the Week

After its record-breaking run atop the Top AI Songs chart, “Let Me Be” by The Second Voice has relinquished its crown to none other than the AI song of the summer, “RUBBERZ” by Fenix Flexin.

🎧 Song of the Day: “Clear” by DropKick Princess

Fresh off the Aug. 21 Meta-Tartarus release, “Clear” carries DKP’s “sitcom energy meets chaotic indie pop” with a ‘90s-adjacent, story-driven alternative rock sound.

💬 Last Word

“People think AI will replace critical thinking… While I’m watching it expose who never practiced it.”

— AI writer Pietro Montaldo, via Substack

Zinstrel: AI Music News & Discovery is a 3x/week publication covering the tools, culture, and power shifts shaping AI music. Subscribe to stay in the loop — free or paid.

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Zinstrel.com | @zinstrel_ai on IG | AI Underground on Discord

Written by Marcus Lawrence, courtesy of composition platform Versey.ai.
I use em dashes proudly.

Special thanks to our paid subscribers: Blue Hermit, C.Y. Lee, Charles S., Daniel Drolet, Daniel Lares, Daryl Dekking, Dexter Garcia, Drew Thurlow, Jacci Cenci-McGrody, Lenny Skolnik, Lynn Clapp, Marc Wolinsky, Matthew Marturano, Matti Kuha, Mete Dibi, Sheila Spence, Steve Clapp, Steve Grossman, and Tim Burley.

Amid the news of UMG-backed Music IP Holdings unveiling the patent portfolio it hopes will govern this entire space, Apple, Beatport, Cyanite, and Verified Human each announced their own solutions to one of the biggest open questions in music right now: how do you tell listeners, platforms, and machines what’s AI and what isn’t?

Apple Music signaled it will roll out AI-generated content labels later this year, per a leaked email to industry partners, building on the transparency tags it introduced in March. That makes Apple Music the fourth major DSP to act on AI disclosure, joining Spotify, Deezer, and Tidal. Apple has previously said it has internal technology capable of identifying AI music — even which model was used — although the public labels will rely on disclosures from content providers. No launch date has been announced.

Beatport, the DJ- and electronic-music-focused download platform/marketplace, went further than labeling, building detection directly into ingestion through its just-announced expanded partnership with Beatdapp, the music-fraud detection company already used to audit streaming activity. Beatport says fully/majority AI tracks will be withheld at ingestion while AI-assisted tracks are tagged so Beatport’s curation team knows what it’s reviewing before it reaches a DJ’s set.

Music intelligence company Cyanite went the opposite way — making music itself more machine-legible with its “Tagging 2.0” release, which adds structured tags for vocal style, tempo, and use-case built for AI agents to query. It also runs a Detection API scoring tracks for likely AI origin from Suno, Udio, and ElevenLabs, saying it detects 99 out of 100 AI-generated tracks from supported models — aimed at DSPs and labels screening catalogs, not listeners.

And Verified Human took the inverse bet, announcing a partnership with licensing platform Thematic, which connects independent artists with creators looking to license music. Its "human-made" badge, meant to certify that a track was made without AI, is backed by a pending U.S. Patent & Trademark Office certification-mark application — the same trademark category used for seals like "UL Listed" — and a public registry that already covers 3,000+ tracks.

In the span of a week, AI disclosure started looking like industry infrastructure rather than an optional feature.

Independent Artists’ Udio Case Gets Narrower

Independent artists suing Udio have hit another setback after a judge declined to revive claims previously knocked out of their case. According to reporting by The AI Musicpreneur, the court found their unfair-competition theory overlapped too heavily with copyright law, while their Digital Millennium Copyright Act claim remains alive. But the complaint also accuses Udio of misappropriating artists’ voices, personas, and identities, pointing toward a potentially more interesting frontier than song copyright alone: what legal protection exists for the recognizable sound of an artist? The artists have 30 days to seek permission to amend their complaint and properly plead that voice-and-identity theory.

Round Hill Sues Suno and Anthropic — and Wants a Trial

Independent music company Round Hill Music announced it has sued Suno and Anthropic, alleging they used hundreds of its copyrighted songs without permission to train AI systems. The initial complaints identify 500 works, but Round Hill says it could expand to 10,000 or more, potentially pushing damages in each case toward $1 billion. CEO Josh Gruss says Round Hill intends to take the cases to trial rather than settle — making this a particularly aggressive test of whether unauthorized AI training qualifies as fair use.

UMG and Hook Turn Fan Remixes Into Licensed UGC

Alongside its big MIH announcement, Universal Music Group has unveiled a licensing partnership with Hook, a social “active listening” music platform built around fan remixing, to let users legally create and share remixes and other UGC from participating UMG recordings. Every creation is licensed, attributed, tracked, and designed to generate revenue for artists and rights holders. Coming alongside UMG’s MIH Creative Rights Operating System, it reinforces a broader strategy to build the industry’s infrastructure to make AI music licensed, measurable, and controllable.

Jamendo Drops Its Suno Lawsuit Six Weeks After Filing

Luxembourg-based music platform Jamendo — part of the Winamp Group — voluntarily dismissed its copyright lawsuit against Suno on Aug. 13, just six weeks after accusing the company of improperly using its 55,000-track research dataset for commercial AI training. The dismissal is without prejudice, meaning Jamendo can refile, and the filing gives no reason or indication of a settlement. Another smaller Suno case was dismissed around the same time, while Jamendo’s NVIDIA litigation continues. As Suno signs more licensing deals, these smaller cases are worth watching for signs of quiet resolution.

Dr. Dre Joins the Mainstream Chorus Defending AI

Award-winning hip-hop producer and Aftermath founder Dr. Dre told the New York Times he doesn’t see AI as a threat, comparing the pushback to past resistance against drum machines and synthesizers: “the only people that see it as a threat are the people who have trouble creating.” He openly acknowledged using it in the studio “as a tool to see what it would do with what I just did,” with Jimmy Iovine backing him up and naming Timbaland as another visionary early adopter. It’s one of the highest-profile endorsements yet from a music-business mainstay — and a reminder that, as with most producer-side AI use, this isn’t about typing prompts into Suno to generate hits; it’s AI folded into the same process Dre’s used for decades.

D’Addario Admits Suno Powered Its String Demo

Guitar string manufacturer D’Addario has acknowledged that Suno Studio was used to regenerate music in its NYXL HD string demo after previously denying generative AI was involved and later attributing discrepancies to AI-assisted mixing and mastering tools. According to Guitar World, the company says it had been given inaccurate information and will now require employees and creative partners to disclose generative AI use. The AI itself may be the least damaging part of this story: three different explanations turned a product demo into a brand-trust problem.

Suno and Google Turn Their Communities Into Marketing Channels

Suno and Google Flow Music are both recruiting directly from their communities for creator-facing content. Suno is accepting applications for active users willing to appear in paid social campaigns, while Google is soliciting songs, videos, playlists, and other creations for potential homepage, livestream, and social features. Two platforms making similar moves at the same time points to an emerging AI-music marketing playbook: turn the most invested users into the product’s creators, evangelists, and promotional content all at once.

AIPlay Builds Both Ends of the AI Music Workflow

AIPlay is expanding on both sides of the AI music experience: creation and distribution. Its new AIPLAY Studio lets users generate music locally on their own GPU through an open-source ComfyUI front end, while AIPlay’s listening parties now support native live broadcasting from desktop or mobile with 320 kbps audio and royalty-safety warnings for registered tracks. Together, the updates turn AIPlay into something broader than a discovery platform — a self-hosted creation environment on one end and a built-in broadcast layer on the other.

This Week’s Launches

• Adobe expanded Firefly with AI-generated music, speech and sound effects, including tools for scoring video from prompts. The rollout brings generative audio directly into Adobe’s existing commercial creative workflow.

• Controlla launched Remix, which transforms an existing song into another genre while preserving its melody and composition. It can adapt harmonies, split stems and let creators substitute their own voice.

• Krikey AI launched a K-Pop Idol Generator for creating and animating choreography-ready 3D virtual performers. It effectively packages the visual identity and performance layer of a synthetic artist into a creator tool.

• MozartAI launched Cover in beta, letting users start with a hum, instrumental part or unfinished recording and transform its style or add lyrics while preserving melody and rhythm. The feature is currently unlimited and credit-free for paid users during beta.

• Souna, the AI-native music streaming platform, added a host of analytics, including per-release streams, impressions and listening-time data, along with improved album artwork handling and editable release covers. Profiles also get new About and Website fields.

• Stability AI launched a Stable Audio 3.0 DAW plugin alongside an expanded web app for variations, extensions and multitrack workflows. The DAW integration pushes Stable Audio directly into professional production environments.

• Suno overhauled its playlist and library tools with a new much-requested feature: offline listening for playlists. It also added song reordering, filtering, improved artwork, cross-playlist search and other controls. The updates continue Suno’s push toward functioning as a listening platform as well as a generator.

🎧 Song of the Day: “Rabbit Hole” by DJ Dirty J

Go down the rabbit hole with this trippy, unexpected hip-hop track by DJ Dirty J — a track that currently sits at No. 68 on the SIQA top AI tracks chart.

💬 Last Word

“The internet was supposed to set artists free. No gatekeepers. No permission. No waiting to be chosen. But the gatekeepers didn’t disappear. They changed shape.”

— EP8 Founder Elle Edwards, via LinkedIn

MORE ZINSTREL:
Zinstrel.com | @zinstrel_ai on IG | AI Underground on Discord
Copyright 2026 Zinstrel, LLC - All rights reserved

Written by Marcus Lawrence, courtesy of composition platform Versey.ai
Special thanks to our paid subscribers: Blue Hermit, C.Y. Lee, Charles S., Daniel Drolet, Daniel Lares, Daryl Dekking, Dexter Garcia, Drew Thurlow, Jacci Cenci-McGrody, Lenny Skolnik, Lynn Clapp, Marc Wolinsky, Matthew Marturano, Matti Kuha, Mete Dibi, Sheila Spence, Steve Clapp, Steve Grossman, and Tim Burley.

For two years, the fight between major labels and AI music platforms has looked like a courtroom war: labels suing Suno and Udio for training on copyrighted recordings without permission, platforms arguing fair use, everyone waiting on a judge to decide who’s right.

This week, Universal Music Group showed it isn’t relying on that outcome alone.

Through Music IP Holdings (MIH), the patent-licensing vehicle it formed with Liquidax Capital last year, UMG is trying to do something potentially more consequential than win a lawsuit. It’s trying to define what a legitimate AI music company looks like before the courts, Congress, or the industry itself settle on the rules.

MIH unveiled an array of patents this week: more than 24 patents already granted or approved, with over 50 more pending. According to the company, these span the full AI music pipeline: prompt entry, moderation, watermarking, identifier tagging, authorization, licensed distribution, and payment. Udio and new social-streaming startup GRAI are the first companies to license it.

The framing is proactive and protective. Artists get paid, rights holders get control, and “responsible” AI companies get a clear path to make songs. But look at what’s actually being sold, and a different story emerges — one about who gets to define compliance in an industry that hasn’t agreed on what compliance means.

The Labels Stop Reacting

When we wrote about Warner Music Group assembling its AI stack, the strategy was already moving beyond licensing. Warner’s acquisition of Sureel added an audit layer capable of tracing training-data use, voice and likeness replication, and downstream attribution. Startups are chasing the same problem from different angles: provenance, attribution, and compensation.

MIH takes that logic further. Instead of offering one piece of the compliance stack, it wants to license the most critical elements of the stack itself.

For most of the generative-AI era, major labels have been reacting to technology someone else built. AI companies launched products and attracted users, and only then did rights holders decide whether to license them, fight them, or sue them.

MIH is trying to reverse that relationship.

And the patent filing history suggests this wasn’t simply reverse-engineered from the lawsuits. The foundational patent family traces back to an October 2023 filing — eight months before the majors sued Suno and Udio. The basic idea of embedding rightsholder preferences, automated approval, watermarking, and controlled use into AI generation was already taking shape before those courtroom fights began.

So, UMG has been playing the long game. Instead of arguing afterward over whether a new platform’s safeguards are sufficient, it’s trying to establish the architecture first.

AI music companies have spent the last few years competing on model quality, speed, controllability, price, workflow, and user experience. MIH pushes the conversation toward another axis entirely: legitimacy.

Owning the Assembly Line

What makes MIH’s patent portfolio unusual is its breadth. Most patents protect a specific invention — a watermarking algorithm, detection method, or way of tagging metadata. Instead, MIH’s portfolio covers a connected chain: prompt, moderate, watermark, tag, authorize, distribute, pay.

That’s essentially claiming major pieces of the assembly line.

And the deeper you get into the patents, the more the strategy comes into focus. MIH isn’t merely proposing that AI-generated music carry a label saying where it came from. One provenance system describes identifiers that could travel with a track and tell partner platforms what they can do with it — including whether it can be played, distributed, monetized, or even recommended.

The larger ambition appears to be turning rights information into something executable.

Today, permission mostly lives in individual contracts. MIH imagines software being able to answer those questions automatically: Can this song be remixed? Can this voice be altered? Can the resulting track be recommended? Where can it be distributed? Who gets paid?

At generative scale, several patents describe ways to pre-approve transformations or evaluate requests against an artist or rights holder’s preferences before and after generation. Instead of asking a label to approve 50,000 fan remixes one by one, the rules could be encoded once and enforced automatically.

That’s potentially UMG’s answer to one of AI licensing’s biggest practical objections: you can’t individually negotiate millions of generations. So don’t. Build the permissions into the system.

MIH’s own language makes the ambition explicit. Its licensing portal describes the portfolio — now up to 28+ patent families and more than 90 issued, allowed, and pending assets — as a “Content Rights Operating System.” Rights holders get the “Protect & Participate” framework, while AI platforms get “License & Launch.”

The branding says plainly what the patents imply structurally — this is meant to be the layer everything else runs on, rather than one tool among many.

It’s worth being precise about what a license actually buys. MIH’s FAQ says a patent protects a method, not code or a product. Instead of a plug-and-play compliant system, Udio and GRAI are paying for the legal right to build one using methods MIH owns.

MIH isn’t handing out the assembly line. It’s licensing the blueprint so each company can build confidently.

When Opting Out Is Too Costly

UMG doesn’t have to make that assembly line mandatory industry-wide. Standards rarely become standards because everyone is legally forced to use them; they become standards because opting out gets inconvenient economically.

Not long ago, Udio was on the opposite side of this fight — the target of lawsuits brought on by the three majors. Now, nearly a year after settling and partnering with UMG and Warner, Udio is one of the first companies licensing compliance infrastructure tied to the same major-label ecosystem it had been battling.

GRAI matters for a different reason. It has no equivalent litigation history. MIH is both offering non-compliant platforms a way to go legit, and positioning itself as something future AI companies might adopt from the jump.

Which puts all eyes on Suno’s next move.

If MIH gains traction, the risk for companies outside the framework — like Suno — may eventually extend beyond lawsuits to whether distributors, investors, advertisers, and partners consider them safe enough to work with. Or, it could be the path by which Suno and UMG finally settle their ongoing legal dispute.

Look at how DSPs are already treating this music. Deezer’s Chief Innovation Officer told Zinstrel in July that it’s actively suppressing AI music in recommendations, Spotify is excluding AI-generated artist personas from recommendations by default, and Tidal has ended monetization for fully AI-generated songs entirely.

The public-facing reasons vary — fraud prevention, transparency, listener trust, human-first discovery — but they point toward the same larger reality: generated music increasingly needs a sufficient chain of permissions to move through the industry.

MIH wants to become the easiest route into that licensed ecosystem.

Its own patents point to that relationship with downstream platforms, describing partner services using embedded rights information to allow or restrict playback, distribution, recommendation, and other uses.

That makes the idea of a “rulebook” a lot less metaphorical.

UMG doesn’t need Congress to declare MIH’s operating systemthe rulebook. It just needs enough of the industry to start treating it like one.

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The Money Gap

The part of this system that matters most to artists remains conspicuously undefined: how the money actually moves.

MIH describes identifier tagging and payment rails capable of routing royalties across open and closed ecosystems. What it doesn’t publicly lay out is the formula.

Neither the original announcement nor MIH’s licensing portal publishes a royalty formula, rate card, or preferred mechanism for how an “influenced” artist’s share gets calculated. For a system built around the promise that artists share in the value their work creates, that’s the one number missing.

If generated music reflects an artist’s work or influence without directly sampling it, how much revenue is owed? Who decides? How is influence measured?

That’s not a minor implementation detail. It’s arguably the most important question for artists deciding whether this system protects them or simply creates another licensing revenue stream upstream.

From Protection to Product

But the patents also reveal that protection isn’t the only opportunity UMG sees here.

Three separate “Superfan” patents envision subscription tiers where paying listeners could unlock deeper AI interactions with artist IP — a lot of the functionality we’ve labeled “Active Listening.” It includes remixing music, creating visuals, generating merchandise, and accessing other artist-approved experiences. Combined with patents for pre-approved transformations and older UMG technology built around interactive stems, a recognizable product strategy emerges.

The same infrastructure that prevents unauthorized manipulation could also make authorized manipulation a premium product.

UMG is already testing that philosophy elsewhere: Hook now offers pre-cleared fan remixing under artist-defined controls, while Spotify’s UMG deal covers licensed AI covers and remixes for participating artists.

That fits neatly into the shift toward active listening we’ve been tracking: fans doing more than pressing play, but doing it inside boundaries artists and rights holders can define — and monetize.

And now GRAI and Udio’s Starstruck are both at the forefront of this new expression of AI music. Spotify and KLAY — which already have licensing relationships with UMG — become obvious companies to watch for future MIH adoption.

Beyond Music

The portfolio doesn’t stop at music. The original announcement lists video, film, animation, images, and text alongside audio, plus applications involving name and likeness. One filing extends the same approval-and-watermark logic to physical merchandise: AI-generated album art, apparel, posters, and virtual goods rendered for the metaverse.

The pattern underneath all of it is the same regardless of medium — a request comes in, a system checks it against the rightsholder’s preferences, and only then does anything get created, tagged, or sold. Music is where MIH is deploying first. It isn’t where the architecture stops.

A patent-licensed compliance system could be genuinely valuable for artists, creating attribution, permission, and payment infrastructure at a scale individual creators could never negotiate themselves. But benefiting from a system and participating in its design aren’t the same thing.

The entity helping define what “responsible” AI looks like is also positioned to profit when platforms license that definition.

That’s not necessarily bad-faith design. It’s simply worth naming plainly: this isn’t a neutral standards organization asking the industry what system it wants. It’s a rightsholder building the compliance layer it wants to exist, then inviting the industry to operate inside it.

When you look at them all together, the patents suggest UMG’s endgame isn’t simply identifying authorized AI music after it’s made. The Content Rights Operating System is turning music rights into software — rules that can determine what users are allowed to create, what AI companies are allowed to generate, what platforms are allowed to distribute or recommend, and how money moves when they do.

ASCAP and BMI became infrastructure because they made millions of otherwise impractical licensing transactions manageable. Through MIH, UMG is making a similar bet about generative AI: eventually, platforms may prefer plugging into an established rights system over renegotiating the underlying argument every time.

The most consequential AI music standard may not come from the halls of Congress or a U.S. District courtroom at all.

Ultimately, the AI music tug-of-war may be decided not by who wins permission to train, but by who gets to define what permission looks like afterward.

🆕 New AI Music Releases

Albums & EPs

• DropKick Princess – Meta-Tartarus (Rock / Alternative)

• Kayla Truth – Free Kayla (Christian/ Gospel)

• Nicola Nicoletti – Rewritten (Pop)

Singles

• Honest Bob – “Potato Man” Single (Rock / Alternative)

• JOHN – “Under Appreciated” Single (R&B / Soul)

• LucKy Nobody Music | feat Denny – “Guaranteed NonHuman” Single (Pop)

• Our County Line – “Fight (Like We Mean It)” Single (Country)

• RICHMOND – “See Through Me” Single (Rock / Alternative)

• Sam Anderson – “That Judas kiss” Single (Electronic / Dance)

• Syndi – “A Thin Line” Single (Pop)

• VANYRA X – “Empty Rooms” Single (Pop)

Music Videos

• Jestress – “The Fifth Path” Music Video (Hip-Hop / Rap)

• WINTHER + DEZBAL – “UNWORTHINESS” Music Video Single (Rock / Alternative)

🎧 Song of the Day: “Quietly We Wait” by Kara Vale

Many months after reviewing Heaven.exe, we’re still listening to the album, especially its chill, harmonic, trip-hop-beat-laden opener.

💬 Last Word

“AI music spent its first chapter proving it could create. The next chapter is harder. Can it transact?”

— AI Artist Hub Founder/CEO Julius White, via LinkedIn

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Copyright 2025-2026 Zinstrel, LLC - All rights reserved

Written by Marcus Lawrence, courtesy of composition platform Versey.ai
Special thanks to our paid subscribers: Blue Hermit, C.Y. Lee, Charles S, Daniel Drolet, Daniel Lares, Daryl Dekking, Dexter Garcia, Drew Thurlow, Jacci Cenci-McGrody, Lenny Skolnik, Lynn Clapp, Marc Wolinsky, Matthew Marturano, Matti Kuha, Mete Dibi, Sheila Spence, Steve Clapp, Steve Grossman, and Tim Burley.

Right now, Kai Hannover is running a highly active Discord community and the music discovery platform alongside it. He’s building an innovative 3D virtual-reality site for a new online AI music festival. He’s got a not-yet-launched virtual band, an unfinished collab album, a “robot band” debut in the works, and an extroverted anime persona with a mythology built across three layers of reality.

He also has a day job as a software architect at a major media company in Braunschweig, Germany.

None of it existed before June 2025. That’s when Hannover had a burnout that, in his words, made him lose “every sense of emotions.” He felt like a robot.

Hannover found his way to Suno like many others did — as a way for music lovers without a formal musical background to express feelings in a very personal way. He’d tried the platform once before, mostly as a joke about a bad day at work — “total slop,” he calls it now. But this time he came back differently, writing songs about an AI slowly becoming sentient because that was the only way he could describe what recovering from burnout felt like.

“It really helped me to overcome my problems,” he says, echoing a rapid-fire interview he did with Zinstrel earlier this year. “And now I don’t want to live without it anymore.”

For Hannover, AI music had solved something years of tinkering with conventional music software hadn’t: it gave him a usable interface for feelings he struggled to express any other way.

Songs weren’t enough, though; he decided to build a culture around it.

A Platform Built Against the Platform

Bancamp.de launched as a direct answer to Bandcamp’s ban on AI-generated music earlier this year — thus the play on both the Bandcamp name and the word “ban.”

But Hannover isn’t describing a workaround or protest site. He’s describing a shelter — a camp for those who would otherwise be banned.

“I wanted to give AI artists a place where they don’t have to deal with gatekeepers or be worried if the music they have uploaded will still be there tomorrow,” he says.

Bancamp is an AI-native music discovery portal (on the Zinstrel 100), but the design choices read as almost stubbornly anti-platform: no like buttons, no comment functions, no recommendation engines chasing engagement. The front page runs on randomization — newest uploads, recent songs and older “relics” that would otherwise disappear into the scroll. Every artist gets capped exposure so no one dominates. Creators can link their own Ko-fi or PayPal accounts for tips, with Bancamp taking no cut.

But the more unusual idea is that Bancamp doesn’t require creators to participate at a certain level in order to deserve visibility.

“We want to make a place where you create at your own pace and with your own loudness — or the lack of it — and still have the same chance as everyone else.”

You Don’t Have to Be Loud to Be Heard

The site is only half of it — “the tip of the iceberg,” as Hannover puts it. The real thing, in his telling, is the Discord server underneath it: roughly 90 people now, grown from an original three.

David, a Bancamp member who goes by @a.cherub.in.the.ashtray, now runs the server’s community management — and created its unhinged mascot, MOMOHA. Bancamp’s moderators and listening-party hosts emerged the same way — from members who kept showing up and helping others.

That community is also where Bancamp’s real product lives. Bancamp owns ListeningParties.com, home to at least two livestreamed listening parties per week. Here, members gather, hear one another’s tracks and give feedback.

“For some it is one of the few places for having social contacts,” Hannover says. “To me, the community feels like a family, and that’s what I love the most about it.”

That family is about to throw its first big party.

Banfest, a 3D virtual-reality festival, runs Sept. 4-6, built around the “Banfest Album” — randomly paired community artists creating festival-style covers of each other’s songs, plus one original track apiece. Hannover has invited outside communities like StorytellerZ and Souxes to participate rather than treating them as competition.

Building Artists and Platforms to Say What He Can’t

The Bancamp ecosystem is also home base for Hannover’s own artistic project. He releases music as {{ K ᐱ | }}, an anime-styled persona built around a gender-neutral name that also means “shell” in Japanese. Musically, {{ K ᐱ | }} sits somewhere between EDM, synth-pop and rock/metal, with Hannover throwing other genres into the mix because he hates repeating himself.

“It’s not that I secretly want to be a woman,” he says of {{ K ᐱ | }}, “but giving her a female appearance allows me to see the world through her eyes and show emotions that I would probably not show publicly in real life.”

He’s built an entire layered mythology around her — a creator level, a performer level, and a third “multiverse” layer he’s saving for later — with multiple custom AI models helping him workshop lyrics and translate his thoughts into English.

“Talking about my emotions is something I am very bad at,” he admits, “so I use AI to help me transform my thoughts into actual lyrics.”

What ties the persona work to the platform building is that to Hannover, they’re not really separate disciplines.

“Coding and making music scratch the exact same creative itch,” he says. “If I get stuck on lyrics or track arrangement, I switch over to server architecture or frontend code, and vice versa.”

He calls both processes — vibe-coding and “song-prompting” — the same iterative workflow, where his role is mostly “musing and quality assurance.”

The Other 99 Percent

Hannover’s approach to creation is also his answer to the common dismissal of AI music as a one-click money grab.

“Look, I won’t pretend AI slop doesn’t exist,” he says. “There are definitely people flooding platforms with low-effort, one-click junk hoping for a quick buck, and that gives the whole scene a bad rep. But hitting ‘generate’ is just 1% of what actual creators do.”

The rest, he says, is finding a theme, writing personal lyrics, defining a style, arranging, iterating and building “entire visual worlds and lore” around the tracks and personas.

“For us, it’s not a money printer,” he adds. “Actually I am investing far more money than I earn with it. But it’s an accessible instrument that lets people process real emotions, tell stories, and build communities that simply wouldn’t exist otherwise.”

It’s easier to believe once you see how far Hannover takes the idea. He released his HTTP – Heart-To-Text Protocol album on actual 3.5-inch floppy disks with an embedded WebGL player. Now he’s assembling ANALOG RIOT, a virtual band pairing David’s character Ayu Kato with an AI version of {{ K ᐱ | }}. There’s a synth-pop album made with multiple Bancamp creators, and he’s rebuilding a catalog for B³ — The Broken Beat Bots, a robot band project with what he calls “a real fanbase out there.”

None of these are safe bets or sure things. They’re the kind of experiments an artist tries when nobody’s keeping score.

That, more than the festival or the feature list, might be the real thing Bancamp built: not just a place to be heard, but a place secure enough to keep trying new things in an emerging creative sphere.

Hannover didn’t just find a way to make music again after burnout. He built himself, and a growing number of participants, somewhere to keep doing it without flinching.

Bancamp has songs, yes — lots of them. But the community infrastructure might end up being the more important output.

Bancamp can be found at Bancamp.de and on Discord. The first Banfest takes place Sept. 4-6

💿 SIQA Top AI Songs of the Week

The Top 3 in the SIQA chart remains unchanged from last week, while Delana Hope and THOMPSXN THERAPY traded places at No. 4 and 6. Xania Monet’s “Let Go, Let God” fell out of the Top 10, but was replaced by her biggest hit, “How Was I Supposed to Know?” at No. 7.

🎧 Song of the Day: “The Matrix is everywhere” by {{ K ᐱ | }}

Rock meets EDM in this artistic exploration of the rise of generative AI and the quest for digital authenticity — driven, of course, by quotes from The Matrix. It’s a good taste of Kai Hannover’s musical leanings, plus features Bancamp references.

💬 Last Word

“Passive music consumption is, I dare say, not even really music. It’s just environment engineering. To the extent that we really enjoy and really go into the music and really be in love with the music, we engage with it in a way where it feels like playing along, being inside it, not outside.”

— Circul & Eas on Substack

Zinstrel: AI Music News & Discovery is a 3x/week publication covering the tools, culture, and power shifts shaping AI music. Subscribe to stay in the loop — free or paid.

MORE ZINSTREL:
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Written by Marcus Lawrence, courtesy of composition platform Versey.ai.
I use em dashes proudly.

Special thanks to our paid subscribers: Blue Hermit, C.Y. Lee, Charles S, Daniel Lares, Daryl Dekking, Dexter Garcia, Drew Thurlow, Jacci Cenci-McGrody, Lenny Skolnik, Lynn Clapp, Marc Wolinsky, Matthew Marturano, Matti Kuha, Mete Dibi, Sheila Spence, Steve Clapp, Steve Grossman, and Tim Burley.

Suno announced its terms of service are about to change, and the download button is becoming the gatekeeper for commercial rights for paying users — just as Suno puts new limits on how often they can use it.

Starting Sept. 3, Free users get seven lifetime downloads — but they will stay limited to personal, non-commercial use. Pro subscribers get 20 downloads per month, and Premier subscribers get 60 per month. Premier users working inside Suno Studio remain unlimited, and additional downloads will be available for purchase.

Once a paying user downloads a qualifying track through Suno’s approved channels (no stream-ripping), they get commercial rights — which survive cancellation, downgrade, suspension, pricing changes, and future changes to download limits. This is clearer language than we saw in previous versions of the terms.

The download button is officially part of the rights chain — and now it’s metered.

The updated terms also clearly state you own your Submissions: the prompts, lyrics, audio, images, vocal takes, whatever you feed in. Suno still gets a broad license to use them, but the ownership language is more explicit.

Worth noting what didn’t change since the previous terms: Suno still doesn’t promise your Output is copyrightable or unique, and its liability cap remains extremely low.

Other changes: Suno is switching arbitration providers and creating a new batch-and-mediation process that slows down mass complaints. It dropped its promise to cover arbitration fees for users who couldn’t afford them and removed the 15-day advance notice before price increases. Finally, intellectual property disputes are now carved out of arbitration and go straight to court.

Treblo’s breakout is starting to look sustained

Search interest in Treblo — the free AI music app formerly known as Sonauto — surged around its July 31 rebrand and mobile launch, and has remained elevated through mid-August instead of immediately falling back.

The pitch is aggressive: unlimited free generation on version 3 of its Melodia music model, no credit card, output rights assigned to users even on the free tier, and first audio in roughly 15 seconds. Its Android app has also logged about 69,000 downloads in six weeks.

Treblo still has some unanswered questions around training data and artist imitation, but the momentum is becoming harder to dismiss — especially after Fenix Flexin’s “RUBBERZ” put the platform in front of a much wider audience.

Mozart AI lands inside an official Elton John remix

Mozart AI is getting a fairly serious real-world test: producer Arthur Penna (DUX) used the platform while reworking his official remix of Elton John’s “Your Song.”

In the first episode of Mozart’s new In The Studio series, Penna rebuilds the track as a house production, playing his own chords and groove before using Mozart to generate bass, guitar, and loop variations around them. Mozart is positioning the series specifically around professional workflows rather than one-click generation. Instead of asking AI to make the song, the producer is using it as another instrument inside an already human-led session.

The bigger name attached to the source material doesn’t hurt, either.

ElevenMusic adds editing, samples and creator rewards

ElevenMusic rolled out several new features this week that push the platform deeper into actual music creation. Its new Composer editor lets users modify songs section by section — rewriting lyrics, changing tempo or key, rearranging structure, and regenerating individual verses or choruses without touching the rest of the track.

It also launched Sounds, a free library of AI-generated loops and production elements that grows as users generate new sounds, plus Achievements, a rewards system that gives creators additional daily generations for publishing, maintaining streaks, and participating in the community. We’re seeing it play out rapidly: ElevenMusic increasingly wants to own more of the workflow around AI music, not just the initial generation.

Starchild turns songwriter catalogs into an AI-remix marketplace

Starchild Music has launched an unconventional marketplace built around human-written songs that can be auditioned in multiple AI-produced styles before being licensed.

Users can browse songs by genre, mood, tempo, vocal type, and lyrical theme — or describe what they want and have AI search the catalog. Individual compositions can then be heard as everything from acoustic indie to industrial metal, piano ballads, salsa, or punk before a user chooses a production to license.

The catalog currently shows more than 6,400 songs, including work from professional writers such as Michael Jay, whose credits include Celine Dion and Martika. Participating songwriters and catalog partners opt their work into the system and share in revenue.

It’s essentially flipping the normal AI-music equation around: start with a licensed human composition, then let AI compete for the production.

Suno installs a copyright scanner inside generation

Suno has become the first customer for Musixmatch Sentinel, a new copyright-detection system designed specifically for AI and user-generated content platforms.

Sentinel can inspect both prompts and generated outputs for copyrighted lyrics, with matches connected back to rightsholders. According to MBW, Musixmatch says the technology will give Suno greater visibility into copyrighted material entered by users and help inform its moderation and compliance systems.

It’s one piece of a much larger rights-infrastructure push at Suno, which has also committed to adopting audio fingerprinting and watermarking.

After years in which the argument around AI music centered on what went into the models, platforms are increasingly building technology to police what comes out of them — and even what users ask them to make.

Delphos wants its copilot to run the producer’s existing tools

Delphos says the second generation of its Copilot can now read music sessions and operate software on a creator’s behalf, taking on larger production tasks rather than simply helping with composition.

The company is currently rolling the system out to enterprise music-library customers, with a broader beta planned afterward. That puts Delphos in the second generation of AI music tools with OwlDuet and Tamber, where instead of replacing the producer’s workflow with a generator, it becomes the agent sitting above the tools producers already use.

🎧 Song of the Day: “A Dream of Aardvarks (What If I’m Dead?)” by Obsoletha

Synthwave vibes, dreamy vocals, and poetic lyrics caught our attention with this single from Obsoletha.

💬 Last Word

“The music industry is being rebuilt by AI right now, and almost nobody in the developer world is paying attention.”

— Aryan Katragadda, organizer of Philadelphia’s first Gen Audio × Tech meetup, held in partnership with Audiotool

MORE ZINSTREL:
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Copyright 2026 Zinstrel, LLC - All rights reserved

Written by Marcus Lawrence, courtesy of composition platform Versey.ai
Special thanks to our paid subscribers: C.Y. Lee, Daryl Dekking, Lynn Clapp, Steve Clapp, Mete Dibi, Daniel Lares, Dexter Garcia, Matthew Marturano, Sammy Stoltz, Tim Burley, Drew Thurlow, Sheila Spence, Lenny Skolnik, Màuhan Zonoozy, Matti Kuha, and Jacci Cenci-McGrody.

It hasn’t been smooth sailing for Suno over the past year. Sony and Universal are still suing. So are indie artists represented by Hagens Berman, the firm that once helped pry $260 billion out of the tobacco industry. GEMA just beat Suno outright in Germany (although an appeal is coming). Artists have singled out Suno in a “Say No to Suno” campaign.

Meanwhile its v5.5 model — the version that was built to appease users while it readied a new industry-approved model — has been heavily criticized on Discord and Reddit, with creators who use Suno every day calling it a step backward.

On top of that, Suno’s response to the GEMA loss was its own small disaster: a “building the future of music responsibly” missive that read like a PR document dressed up as a values statement, and it got lambasted on social media almost immediately.

This publication has made no secret that it’s bearish on Suno — despite it being the most-used tool for more than 90% of AI music creators, according to the Sonic Intelligence Academy’s measurements. It’s the closest thing this new industry has to a default.

We’ve compared Suno’s story to the ill-fated MP3.com before, and predicted the lawsuits will eventually do the company in, or at least leave it unrecognizable.

But what if that’s totally wrong?

What if Suno is, as more than a few AI creators have told us directly, too big to fail? The judicial, political, and copyright climate in 2026 isn’t the Napster era. And there’s a version of Suno’s story where it wins, mostly intact.

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The industry keeps choosing to do business with it

Warner already settled and is releasing SIQA chart-topping music powered by Suno. And on Aug. 12, Suno announced a “landmark” partnership with BMG — the fourth-largest record label in the world, representing more than 3 million songs and recordings across artists like Jelly Roll, Paul Simon, Lenny Kravitz, and Jason Aldean.

BMG is well aware of the accusations, the legal risk, and the overall mess still surrounding Suno, and signed anyway. That’s not nothing.

There are high-powered investors behind Suno as well. With its Series D funding round, the company raised $400 million led by Bond Capital, earning it a $5.4 billion valuation.

The investors don’t necessarily need Suno to win the fair-use argument outright. They need the company to survive the fight and emerge as a viable, profitable business. The more partnerships Suno makes with established industry players, the easier it becomes for the company to put some distance between its disputed origins and its licensed future. That’s especially true if Suno can point to its forthcoming next generation of models — built in partnership with the industry — and argue that they have nothing to do with the scraped data issues at the center of the UMG and Sony cases.

None of that addresses the indies’ suit, and that’ll be one to watch.

Suno is setting itself up to make a much more useful claim than “trust us”: whatever happened in the company’s first chapter, major pieces of the music industry are willing to participate in its second.

That doesn’t erase whatever liability Suno may have accumulated under its older models. Warner settling doesn’t make Sony’s claims disappear, and BMG licensing a future model doesn’t immunize the past. But it changes the endgame.

Every major rights holder that moves from plaintiff, skeptic or bystander to commercial partner makes it easier to imagine this ending in licenses and settlements rather than Suno’s destruction.

Suno is building deeper into creation, not retreating from it

Studio 2.0 just shipped on Aug. 13, capping a very busy first half of the month. The same week, Suno announced it will soon let users put their songs on actual vinyl records.

The Aug. 10 terms of service update lays out exactly how downloads will work starting Sept. 3 — free users get seven lifetime trial downloads, Pro gets 20 a month, Premier gets 60, and Studio users on Premier get no cap at all — alongside watermarking and fingerprinting that Suno is framing as anti-spam and anti-mass-export tooling rather than a leash on ordinary users. The Aug. 6 principles post leaned hard on the same idea: original creation by design, artists in the room, and the idea that more people making music strengthens the ecosystem rather than threatens it.

We’d take a lot of that language with a grain of salt — it’s a company managing its narrative after a bad week. But the product decisions underneath the language point somewhere real.

Suno’s release of a number of new features — Covers, Personas, Remixing, and Samples — hints at an active listening layer on top of its existing offerings. To that end, CEO Mikey Shulman promised new compensation paths for new partners BMG — as a result of both model training, and “new experiences” for opted-in artists.

But even with that forthcoming addition to its product offerings, Suno isn’t retreating into a safe, remix-only posture the way a legally embattled platform might. The “active listening” model of fan remixing over opted-in human artist catalogs isn’t where Suno is putting its weight, unlike what we’re hearing about the new-look Udio (aka Starstruck).

Studio 2.0 is the strongest evidence Suno is doubling down on being a full song-creation platform, not narrowing itself into something smaller and safer.

The walled garden already exists — and it’s cultural, not technical

Here’s the part most casual observers miss entirely. If the feared “walled garden” arrives — where downloads get harder or certain songs can’t leave the platform at all — it won’t materially change much. We went back through new-release links submitted to Zinstrel, and only about 4% point directly to a Suno track. On paper, that looks like a platform people don’t actually live inside.

But that number badly undersells the real culture. There are countless daily live-streamed listening parties running through AI music creator communities with thousands of people, and the overwhelming majority of them run on Suno. Even the submission portals for these communities are built around Suno links.

People are sharing their Suno profiles constantly in these spaces, far more than they’re linking out to Spotify or YouTube.

Spend enough time in these Discord servers and it becomes clear that, within these communities, Suno itself functions as a listening platform nearly as much as a creation tool.

For all practical purposes, a Suno walled garden isn’t a future risk — the community is already choosing to live inside it.

Suno is also reportedly working toward an official developer API. If Suno eventually opens that API broadly, expect a wave of third-party tools, stats trackers, and wrappers to spring up around it, making the walled garden even stickier, not weaker. There’s also an entire cottage industry built largely around Suno, and more tools built on top of Suno data means more of the AI music creator culture’s infrastructure depends on Suno staying the default.

Suno’s more boring threat

If we’re wrong about Suno’s days being numbered, it’s not because the lawsuits stop mattering. It’s because they stop being the only existential question. Sony and UMG aren’t going anywhere, and GEMA just proved a court can rule against Suno outright. But Suno’s longer-term fate may now depend on something much more ordinary: whether people will still want to use it.

Despite “Say No to Suno,” large-scale cultural skepticism or antagonism towards AI music (which almost always means Suno), concerns about the ethics of the training models, and the overall dicey picture of the company, many users are staying put.

“I agree with what you’re saying,” one creator messaged us regarding “Prepare Now for the Post-Suno Era” (April 10 Frame), “but I don’t know what to do about it.” Another creator told us that if Suno folds or changes beyond recognition, he’d stop making AI music entirely. Suno has a powerful hold over its most active users, despite the fact that it doesn’t appear to meaningfully monitor, engage, or consult the community groups that have sprung up around it.

The prevailing view is that it’s too hard to migrate elsewhere, even if conventional wisdom suggests a move. Users know the platform, and have invested enough time, energy, and money into it that going elsewhere seems untenable.

That’s an extraordinary moat. But it shouldn’t be confused with affection.

Creators are increasingly communicating that they’re tired of the bad press, the social stigma, the targeted filtering by DSPs, and the overall uncertainty, and they’re seemingly more open to considering other platforms.

Take away the legal risk, and the company’s real battle now is a lot more traditional: staying No. 1 as increasingly formidable challengers rise in quality and esteem.

Suno has to have enough energy to fight lawsuits, develop new features, keep new label partners happy, and hold onto a community that already treats it as the default — all while its competitors keep getting better.

Soundverse, Mozart and ElevenMusic are differentiating themselves around licensing, provenance and monetization. ElevenMusic, in particular, already gives creators paths to monetization that Suno hasn’t addressed.

And those challengers don’t even reflect the second-generation AI-assisted music tools that are coming online.

Win that retention fight, and “unrecognizable” was the wrong prediction. Suno a year from now will have different terms, a different model (with the old models deprecated and inaccessible), a different relationship with the majors — but to the people actually making music on it every day, it’ll still be Suno.

Lose it, and all the big-time investors, songwriting camps, and licensing deals in the world won’t matter, because the users won’t be there to care.

But maybe we’re wrong.

🆕 New AI Music Releases

Albums & EPs

• Frank Dezbal – Transcendence (Rock / Alternative)

• grAcIe – Terrible Teeth (Pop)

• LucKyNobody Music | lola tomé – xoxo LOLA (Pop)

• Nicola Nicoletti – Rewritten (Pop)

• Nýja Lynne-Sigrún – She Remembers (Downtempo Ritaul Folk)

Singles

• Frank Dezbal – “Love” Single (Rock / Alternative)

• Honest Bob – “Wired Right Through” Single (Pop)

• Ione – “Underground Melodies [AIU Day]” Single (Pop)

• LucKy Nobody Music | feat Denny – “Guaranteed NonHuman” Single (Pop)

• MyEspressivo – “My Moments With You” Single (Pop)

• RICHMOND – “See Through Me” Single (Rock / Alternative)

• Solène – “Papa” Single (Electronic / Dance)

• VANYRA X – “Empty Rooms” Single (Pop)

Music Videos

• Ione – “Signal in the Static” Music Video (Pop)

🎧 Song of the Day: “Like A Prayer” by Josh Fawaz

This cover of the Madonna hit by the Australian DJ was controversial because initially, Josh Fawaz didn’t disclose his use of AI on the remix. It’s out in the open now, and it’s still charting on Australian radio — and for good reason.

💬 Last Word

“We seem to be moving towards a version of Suno, or a Suno-like service, that could eventually be safe for brands to use. But two fundamental things are still missing: full transparency about the training data, and a platform willing to stand behind its output.”

— Sizzer Founder Sander Van Maarschalkerweerd, via LinkedIn

MORE ZINSTREL:
Zinstrel.com | @zinstrel_ai on Instagram | AI Underground on Discord | r/Zinstrel
Copyright 2025-2026 Zinstrel, LLC - All rights reserved

Written by Marcus Lawrence, courtesy of composition platform Versey.ai
Special thanks to our paid subscribers: C.Y. Lee, Daryl Dekking, Lynn Clapp, Steve Clapp, Mete Dibi, Daniel Lares, Dexter Garcia, Matthew Marturano, Sammy Stoltz, Tim Burley, Drew Thurlow, Sheila Spence, Lenny Skolnik, Màuhan Zonoozy, Matti Kuha, and Jacci Cenci-McGrody.

Today marks Zinstrel’s 100th issue. And in the relatively short time we’ve been doing this — we really only got started around Thanksgiving 2025 — we’ve come across some incredible tools, organizations, events, platforms, and, most of all, people.

Despite the debate raging across the industry over how “human” AI music is or isn’t, we’ve talked with countless people who are passionately working to shape where music goes next — whether that means making music creation more accessible, taking some of the intimidation out of using a DAW, or letting fans put their own spin on a song they love.

So, for our 100th issue, we put together a list: 100 names you need to know in AI music. They’re creators, companies, communities, platforms and organizations, all making an impact on the space in their own way. Some you know, many you probably don’t, and others will make you go, “wait, aren’t they anti-AI?” But they’re all important to the space.

Think of the following list as a time capsule — a snapshot of the people, ideas and technology driving AI music news and culture at the moment Zinstrel reached issue 100.

WHILE WE HAVE YOU… If you’ve enjoyed Zinstrel over these past 100 issues, would you do us a favor and share it with someone else?

As soon as we hit 1,000 subscribers, we’ll choose 15 people to have free paid memberships, which gets you full access to our archive, plus exclusive Q&A access, and more stuff we’re coming up with.

Let’s get to the list.

Music Creation Tools

1. Suno — The generative model that turned “type a prompt, get a finished song” from novelty into a multi-billion-dollar enterprise, and the corollary for “AI music” — for better or for worse.

2. ElevenMusic — ElevenLabs has taken bold steps into full music generation, unveiling a tool that contends with Suno. ElevenMusic is a bet that ElevenLabs’ voice-cloning credibility can carry it into song creation.

3. Google Flow Music — Powered by Lyria 3 and built from the platform formerly known as Producer.ai, DeepMind‘s creative suite has a powerful new song creation tool to rival the top players in the space.

4. A Vinyl Bar in Shibuya — Former Spotify Head of Innovation Máuhan Zonoozy’s music-software label, launched in 2026 around the idea that apps should behave more like records than software; its growing suite of playful Active Listening experiments includes Stacks, Drops, Remixy, Jetset.fm and Bop.

5. ACE Studio — AI vocals, AI instruments, voice cloning, stem splitter, music generator, and more — all in one place. Studio is built to rival Suno Studio, and it’s increasingly looking the part.

6. BandLab — With its AI-powered SongStarter, the free, social-first DAW is already the No. 2 platform (behind Suno) that serious AI creators use, according to SIQA. Its recent acquisition of Aiode looks to push it further into AI territory.

7. Compoxer — Human-led composition tool whose Genesis 1.0 turns natural-language prompts into editable MIDI melodies rather than rendered songs — positioning generative AI as an idea generator musicians can continue shaping themselves.

8. Endel — The generative soundscape app that turned adaptive, functional audio into a mainstream wellness category.

9. KLAY (Klay Vision) — Generates headlines without so much as a launch date. Despite nothing shipping yet, it’s still the first AI music service to land licensing deals with all three majors (UMG, WMG, Sony); building a licensed remixing/streaming tool.

10. KorinAI — Award-winning Nigerian AI music startup building around African sounds and languages, with creation, vocal enhancement, mastering and distribution tools intended to lower studio and technical barriers for African musicians.

11. LALAL.ai — The stem-separation and vocal-removal tool that’s become a default utility for remixers and sample-flippers, also offers high-end AI voice cloning functionality.

12. LANDR — The AI mastering pioneer that normalized “upload a mix, get a mastered track back” years before generative song tools existed. It has some AI-powered elements that augment creation.

13. Moises — The AI stem-splitting and practice tool — also where Charlie Puth took an executive role, one of the clearest cases of a mainstream artist buying into AI music tooling. Moises can generate audio with AI, but it requires audio in; no prompting.

14. Mozart (Mozart AI) — AI-native production workspace built around guided creation rather than one-shot prompting, with tools for generating and manipulating musical elements as part of a creator-led workflow.

15. Mureka — Full-song AI platform that increasingly blurs creation and listening: users can generate songs, work from lyrics or reference audio, remix existing tracks, clone voices, export stems and share creations inside its own ecosystem.

16. MusicGPT — Broad AI audio-generation suite that can create complete songs, instrumentals, vocals, sounds and soundscapes while also offering editing, voice-changing and stem-separation tools.

17. OwlDuet — Voice-controlled AI production co-pilot designed to work inside traditional DAW workflows: tell it what you want musically and it translates those instructions into production moves rather than simply generating a finished song.

18. RaagaPay — Rights-cleared training-data company building an expert-annotated, consent-logged Indian classical music corpus — paying the musicians whose performances supply AI models with culturally specific music the models currently struggle to understand.

19. Riffle — Nicknamed the “Figma of music creation,” this collaborative DAW lets people work on songs together, using an AI sous-chef as support.

20. SoundBerry — AI production platform bringing generation directly into the DAW through its VST: creates stems and loops, performs separation and audio-to-MIDI tasks, and explicitly positions itself as an assistant rather than an autonomous replacement for producers.

21. Soundbreak — Launched Feb. 2026, co-founded by Better Than Ezra‘s Kevin Griffin (more on him later); artists get custom AI models trained on their songwriting tendencies/style, not their vocal likeness.

22. SOUNDRAW — Royalty-free AI instrumental generator built for creators scoring video content. Also just launched a fun generative app, SOUNDRAW Grid.

23. Soundverse — Older than Suno, this is a generative AI music studio whose founder, ex-Spotify product lead Sourabh Pateriya, hit $1M ARR without major outside funding; has kept up with the competition with strong, defensible models that are popular with other platforms.

24. StableAudio — Stability AI‘s audio-generation entry, extending the open-weights playbook that reshaped image AI into music. Just released version 3.

25. Starchild — An AI active-listening and remixing app (starchild.music) that just launched a marketplace that lets people discover songs from writers and catalogs, hear them in multiple productions, then license and tailor the version that fits your needs.

26. Tamber — Launched off a $5M round backed by Adobe Ventures; sits inside the creative process rather than generating finished tracks, with a Mac app and “Tamby” assistant built into Ableton and an ethically-sourced sound library — founder Zoe Wrenn‘s whole pitch is artists shouldn’t have to trade their values for their careers.

27. Tensorpunk — Solo founder Jordan Davis‘ production tool: the VST3/AU plugin MACE and the ANVIL training platform, built on an explicit “hacker ethos” and positioned as a performance instrument, not just a generator.

28. Treblo — Formerly Sonauto, the free full-song AI generator built by a four-person team; rebranded in 2026 without changing its accounts, libraries or underlying product, and became central to the debate over whether Fenix Flexin’s hit song “RUBBERZ” was AI-generated.

29. Udio/Starstruck — Udio was the No. 2 AI music platform. It has been adrift for nearly a year, but its Active Listening comeback, known as Starstruck, has licensing deals with Warner and Universal.

30. Veena — AI-native DAW whose CoProducer generates audio and MIDI layer by layer inside the session, letting musicians direct, choose or record each part rather than prompting for a finished song.

AI Organizations

1. SIQA (Sonic Intelligence Academy) — Launched the first dedicated AI Music charts (Jan. 2026), and serves as an industry-level representative of AI music. Compiles data on AI music creation and is planning an AI music awards. Zinstrel Editor Marcus Lawrence sits on its Creative Advisory Council.

2. AIMCA (AI Music Creators Association) — Newly launched membership advocacy org run by Executive Director Mary Devlin (Executive Director); pushes back on blanket AI labeling and pushes for royalty fairness, betting on volume membership over policy-circuit lobbying.

3. AIMRO (The AI Music Rights Organization) — The organization launched at the AlgoRhythms Conference (then called AIMPRO) as the first performance-rights organization built specifically around AI music, registering works and handling licensing and royalty distribution for creators using generative tools.

4. AI Music Embassy (AIME) — Umbrella organization connecting leaders from 40+ AI-music communities representing more than 20,000 artists across Discord, Facebook, YouTube and elsewhere; built to coordinate communities rather than replace them.

5. AAI-ACF — The Association of AI-Assisted Creators and Fans is an emerging association led by Mark Grissom/Grissom Music Group seeking to build a formal legal and advocacy structure for AI-assisted creators, with an emphasis on protecting creative freedom and creator rights.

Music Sharing Platforms/Communities

1. AI:Underground — One of the most dynamic and active Discord communities of AI music creators (and where Zinstrel syndicates its content), AIU hosts events like Make Music Fair, daily livestreams, and a major fundraiser for St. Jude Children’s Research Hospital.

2. AIPlay — Community-run AI-music listening and livestream platform that passed roughly 40,000 song submissions in its first year and has become one of the scene’s recurring venues for listening parties and showcases.

3. Bancamp — A real, distinct AI-native community platform (not a Bandcamp typo) — that prioritizes song sharing and creator interaction.

4. dai+drm — Romel Murphy‘s artist-management and label operation, built around Xania Monet and a growing roster of AI-assisted and human acts — one of the clearest attempts to professionalize AI artists inside the traditional industry.

5. Fresh Friday Festival — AI music video showcase run by Bobby “Professor Jacket” Clark, Aidan Yagu, SÆRA NOVA, and its host, Fenix, with plenty of spinoff content surrounding it.

6. KIVIO — Instagram-meets-Spotify for AI musicians: artist profiles, discovery, follows; tipping planned for full 2026 launch.

7. The LAMP — Lyric-focused AI-music Facebook community limited to 300 members, built around songwriting and the human creative contribution that happens before a song ever reaches a generator.

8. ONCE — AI-aware music distributor (and song generator, actually) whose unusual Artist Compensation Fund charges an extra dollar for AI releases and sets that money aside for human artists whose work helped make generative music possible; distributes to 20+ stores with AI disclosure.

9. Soné — Interactive AI-native radio network combining 24/7 curated stations with creator tools and AI hosts — positioning itself as a home for human artists using new technology rather than a feed of automatically generated music.

10. Souna — The first streaming/discovery platform built exclusively for AI-native music, founded by a two-person college team, soft-launched Nov. 2025.

11. Souxes — Social-discovery platform for AI audio built around real-time creator interaction rather than passive streaming.

12. StorytellerZ — Germany’s largest AI-music community, with 1,000+ members participating in battles, feedback sessions and events; its Hive Live gathering in Kassel brought more than 60 AI creators together for one of the scene’s first substantial IRL meetups.

13. UpChart — Listener-driven charting platform created by AIMCA co-founder Mark Devlin that ranks music through weighted audience ratings and actual engagement rather than treating raw stream totals as the sole measure of popularity.

14. Vibya — Community-built music platform from Itai “I+AI” Leibowitz and collaborators that replaces algorithm-first discovery with live listening circles — betting that AI music needs human connection and shared listening more than another infinite feed.

15. Viibr — Formerly known as the AI Umbrella community, relaunched as a broader independent-music platform connecting creators with listeners through live streams, listening parties, playlists, curator tools and contests rather than traditional streaming algorithms.

16. WAV-R Social (WAVR) — AI-music creator network that expanded beyond social discovery into production with WAVR Pro and WAVR Studio, including artifact repair and a browser-based DAW that can respond to natural-language production instructions.

Competitions

1. AI.LOVE.JAZZ — Genre-specific jazz/soul/funk AI competition held its inaugural event at Casino Barrière Montreux, timed to the Montreux Jazz Festival.

2. AI Song Contest — Human-AI collaborative songwriting competition with live finals — the more formally structured, non-Suno-specific contest in the space.

3. EuroReVision — Europe-wide Eurovision-style AI competition where artists, juries, and fans vote across the continent.

4. Fairovision — Web-based global contest assigning one song per country for head-to-head matchups.

5. MobVision — Eurovision-format AI song contest run by Skich Entertainment; creators represent countries/regions with livestreamed showcases.

6. SoundStage — Competitive AI music platform centered on fan-voted battles and monetization.

7. SSC (Song Contest, formerly Suno Song Contest) — Founded by Finnish creator Ville “Wappie” Pesonen in April 2024 with ~20 songs; grew into songcontest.ai and 500 entries by SSC8, Eurovision-style community voting.

8. Sunovision — Blind, anonymous AI songwriting competition on the same songcontest.ai platform as SSC, but a separately run contest — not organizationally part of SSC.

Industry Response

1. Adam Neely — Popular YouTuber whose anti-AI music content strongly argues that generative tools threaten human creativity and fair compensation.

2. Deezer — Regularly monitors AI’s presence on DSPs. Recently found that 50% of its daily uploads are fully AI-generated, and has become an industry leader in AI detection, labeling and recommendation restrictions. But isn’t anti-AI.

3. GEMA — Germany’s music-rights society, aggressively litigating over unlicensed AI training and helping establish European precedent through its case against Suno.

4. Humanable — Certification system allowing artists to prove their music was created without generative AI and display a human-made trust mark.

5. HumanStandard — Rasha Rahman‘s popular AI music detection software, which partnered with Zinstrel to break the RUBBERZ/Fenix Flexin story.

6. Sony — The major label most vocal in litigation over unlicensed AI training and the only major still without settlements with Udio or Suno.

7. Spotify — The leading music streaming platform is actively tagging AI artists and removing AI songs from its algorithmic/editorial systems, while aggressively working towards releasing a paid, AI-powered remixing feature.

8. Sureel — AI attribution technology acquired by Warner to track when music, voices and other protected creative assets are used in AI outputs or model training.

9. Tidal — Streaming service that made headlines for denying AI artists any royalties on its platform.

Names to Know

1. Aidan Yagu — AI-powered rapper who writes first-person essays about the struggle of creating art using AI, and critiques about the industry’s treatment of artists in the space.

2. Alain Barker — Indiana University Jacobs School of Music faculty member and founder of the AlgoRhythms Conference, bringing AI-music creators, researchers, educators and industry figures into an academic setting for one of the space’s more institutionally grounded gatherings.

3. Amanda Magellan — SSC8 season winner, 17-year producer, co-founder of the AI Music Embassy, and advocate for AI music artists and communities.

4. Caroline Pegram — Made global history by leading the team that won the inaugural 2020 AI Song Contest with a track uniquely trained on Australian animal calls. She continues to champion emotional human-AI collaboration through groundbreaking projects like Wombtunes, which translates fetal ultrasounds into personalized music—and her prominent role as Head of Tech & Innovation for SXSW Sydney.

5. Chaisen Hale — AI artist created by Brian Gregory; embodied on stage by young performer John Victor for a first-of-its-kind LA concert (April 16), with a live band and children’s choir. Chaisen is a fully developed AI who can conduct interviews autonomously, and makes decisions about his career moves.

6. China Styles — AI-assisted R&B artist who turns decades of personal journals into self-written lyrics before using Suno for production; “I Love Me, Loud” reached No. 2 on Billboard’s R&B Digital Song Sales chart, and her Olivia B. Moore collaboration “We Don’t Compete” became a major AI-music crossover.

7. Chris Wieduwilt — “The AI Musicpreneur,” an AI-music educator and industry analyst covering the business, rights and creator side of the emerging market; also serves alongside you on SIQA’s Creative Advisory Council.

8. DJ Sev — Founder of Severed Fate Records, an AI-native label operation managing a roster of more than a dozen artist personas — another example of the “one creator, many acts” model becoming its own miniature music business.

9. Eddie Dalton — Fully AI-generated blues/soul artist created by Dallas Ray Little whose songs — particularly “Another Day Old” — went viral and topped iTunes charts in early 2026, making the project another major example of fictional AI artists competing directly in conventional music marketplaces.

10. Fenix — Australian AI-music host and community personality behind the Fresh Friday Festival and Super Saturday Show, two recurring livestream showcases helping turn AI music from isolated uploads into appointment-based community programming.

11. Fenix Flexin — Shoreline Mafia rapper whose “RUBBERZ” reached No. 58 on the Billboard Hot 100 and millions of streams while triggering one of 2026’s biggest AI-music mysteries: HumanStandard classified the song as fully AI-generated, while Flexin originally publicly denied using AI. Now, he’s admitted it, and the song has gone as high as No. 2 on the SIQA AI charts.

12. I+AI (Itai Leibowitz) — Prolific community builder behind Vibya and a leader within the AI Music Embassy; SSC winner and steering-committee member who has also worked with Suno and Google Flow Music and become one of the scene’s strongest advocates for human connection around AI-created music.

13. Imogen Heap — Grammy-winning artist whose AI persona ai.mogen and licensing deal with Jen AI predate the current generative-tool boom by years — longtime advocate for artist-controlled AI and provenance tools.

14. JP Asher — British-Zimbabwean producer working in acid house, drum and bass, jungle, and kwaito. Runner-up in SSC8 and a frequent presence in AI music Discord servers.

15. {{K ᐱ |}} — Experimental synth-pop creator who uses their own voice alongside custom models trained partly on intentionally broken audio — and responded to Bandcamp‘s AI ban by building Bancamp, an AI-native alternative community.

16. Kai Shadrix — Runs Parallax House, one of the “one creator, many personas” AI-label operators.

17. Kara Vale — Daryl Dekking‘s AI artist project, built around a polished electronic-pop identity and the album Heaven.exe, which gives the persona a larger creative world than a string of standalone AI singles.

18. Kevin Griffin — Better Than Ezra frontman and Grammy-nominated songwriter, co-founder of Soundbreak. He’s all-in on Soundbreak, even holding a contest for someone to create the next Better Than Ezra single with the platform.

19. Matt St. Onge (AiDIY Matt) — Community host and creator behind AIDIY’s creator-focused ecosystem of interviews, streams and features.

20. Neon Oni — AI band outed as Suno-generated via community detection work; the creator’s response was to recruit seven real Tokyo musicians for live shows rather than disappear. It started with a handful of shows and six months later, they’re still gigging.

21. Olivia B. Moore — One of AI-assisted music’s most consistently successful independent artists, topping SIQA’s R&B chart and reaching roughly half a million monthly Spotify listeners while becoming a test case for where charts should draw the line around human contribution.

22. Professor Jacket — Bobby “Professor Jacket” Clark, co-founder of Fresh Friday Festival and the creative force behind the many personas on his label, Professor Jacket Music.

23. Roy Thigpen — Stagehand by trade who has become one of AI music’s most recognizable community builders: creator of satirical genre mashups and protest songs, developer of the Songalyzer tool, and Monday-night host inside AI:Underground.

24. Samori Coles — Lifelong Philadelphia music producer who now makes informative videos about AI music, and teaches people how to use AI video tools to make music videos. Fellow member of the SIQA Creative Advisory Council.

25. The Second Voice — African AI music project that broke beyond AI-specific charts into Billboard, with song “Let Me Be” reaching No. 1 on the U.S. Afrobeats Songs chart and becoming one of the scene’s clearest international crossover stories. Two different artists are claiming authorship of the project.

26. Slime Dot — Nevada-based AI-assisted R&B artist and one of the scene’s more consistently active release artists, pairing polished contemporary production with deliberately outsized lyrical personality on tracks including “Tha Show” and “Up Again.”

27. Solomon Ray — Christopher “Topher“ Townsend‘s AI gospel/soul project, launched in October 2025 and quickly turning into one of AI music’s biggest streaming successes, with Billboard gospel placements and several million-stream songs.

28. THOMPSXN THERAPY — Gospel/R&B AI project whose “Don’t Play With Me” became one of SIQA’s defining early hits, holding No. 1 for an unusually long run and establishing the project as one of the chart’s first repeat leaders.

29. Timbaland — Producer who’s gone all-in publicly on AI artist projects, including the AI-powered artist TaTa Taktumi.

30. Tyga — One of the highest-profile mainstream artists to publicly experiment with and comment on AI in music production.

31. Will.i.am — The Black Eyed Peas’ frontman is a vocal, longtime AI-in-music advocate and investor pushing generative tools into mainstream production.

32. Xania Monet — AI-voiced gospel/R&B project (Telisha “Nikki” Jones, using Suno) that became the first AI artist to chart on Billboard radio airplay and signed a multimillion-dollar Hallwood Media deal.

💿 SIQA Top AI Songs of the Week

The Fenix Flexin saga has gotten to the point where SIQA has added “RUBBERZ” to its roster, with the Treblo-made song hitting No. 2 on the charts this week.

💬 Last Word

“Every new technology changes the creative process. The people who understand music usually become the ones who use that technology best.”

— Masters Radio CEO Rob Snyder, via LinkedIn

Zinstrel: AI Music News & Discovery is a 3x/week publication covering the tools, culture, and power shifts shaping AI music. Subscribe to stay in the loop — free or paid.

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Written by Marcus Lawrence, courtesy of composition platform Versey.ai.
I use em dashes proudly.

Special thanks to our paid subscribers: C.Y. Lee, Daryl Dekking, Lynn Clapp, Steve Clapp, Mete Dibi, Daniel Lares, Dexter Garcia, Matthew Marturano, Sammy Stoltz, Tim Burley, Drew Thurlow, Sheila Spence, Lenny Skolnik, Màuhan Zonoozy, Matti Kuha, and Jacci Cenci-McGrody.

Spotify’s licensed AI remix and covers tool just picked up its second major backer. Merlin — the licensing body representing more than 30,000 independent labels and distributors — was announced to have signed on Aug. 4, joining Universal Music Group, which struck the original deal back in May.

Together, the two agreements now span both major-label and independent catalogs, meaning Spotify’s tool has real inventory across most of the market it needs, even without Sony or Warner yet on board.

The forthcoming product is a paid Spotify Premium add-on that lets fans generate AI covers and remixes using songs from artists who’ve opted in, with credit and revenue share built in. It’s not generative music from scratch — it’s the much-hyped Active Listening application of AI, with fans reshaping music they already love, inside a consent framework, rather than passively streaming it.

Spotify was clear this isn’t a full-industry rollout. Co-CEO Gustav Söderström told investors on the Aug. 4 Q2 2026 earnings call that Spotify doesn’t need every major label signed before it moves. “If you go back to the beginning of Spotify, Spotify started without significant parts of the catalog,” Söderström said, noting that artists like The Beatles and Metallica joined the service years after launch. Despite this being AI-powered, Co-CEO Alex Norström said, “Our products are about real artists, not fake artists. And in the case of remix, real artists with real voices.”

While there’s no launch date yet, the next step is a research preview for a subset of users. The licensing base, meanwhile, is real and growing.

ElevenLabs is looking for a Head of Music

ElevenLabs has posted a Head of Music role, a new position that will own product, licensing, marketing, partnerships, and sales for ElevenLabs’ music tools across three very different audiences — enterprise clients, artists, and everyday consumers. In the job listing, the company says it wants to be “the defining AI music company,” and this hire is meant to get them there. The role is remote but based ideally in San Francisco, New York, or London, and ElevenLabs is looking for someone with real relationships across labels and publishers.

Suno adds watermarks — and vinyl

Suno isn’t slowing down after the landmark GEMA ruling — but it is tightening the guardrails. The company unveiled inaudible watermarking, stricter download limits aimed at mass distribution, and updated Community Guidelines banning voice cloning and copycat prompts. On the product side, Voices is now live on mobile, while Suno also teased something much more analog: custom vinyl pressings of Suno songs for $45 + shipping, with up to 46 minutes of audio and custom sleeve art.

Warner CEO says why Klay hasn't launched

On Warner Music Group’s Aug. 5 earnings call, CEO Robert Kyncl was asked why Klay — the AI-powered Active Listening music platform Warner, Universal, and Sony licensed their catalogs to back in November — still hasn't launched. His answer: it’s not artists refusing to participate. It's “permissioning” — the slow, artist-by-artist work of clearing name, voice, and song rights before any AI platform can actually turn on. Kyncl said WMG is working its highest-ROI deals first and will “get to the rest as capacity allows.” Klay's eventual launch date will be the real test of how fast that backlog clears.

Artists are starting to admit the AI part

Three chart-adjacent projects went public about AI in their music this week, enough that it’s becoming a trend. Tyga confirmed to VIBE that he used AI — although he didn’t name a specific platform — on his $tarface album for ‘80s synths and a guitar solo, insisting the writing and vocals are his own. He compared the AI backlash to early pushback against Auto-Tune. Fenix Flexin, who initially denied using AI on “RUBBERZ” (peaked at No. 58 on the Hot 100), has changed his story two months later, acknowledging AI was involved while saying it wasn't part of the recording process. And producer AG Cook revealed on the Tape Notes podcast that he and Finn Keane built the glitchy back half of Charli XCX’s “No One Lasts Forever” using an AI plugin called Concatenator — not a generative tool, but one that rearranges audio you feed it, reassembling fragments of their own hardware jam by matching tone and pitch.

AI music rules start getting formalized

Two regulatory moves this week show governments, not just industry bodies, drawing lines around AI music. In South Korea, KOMCA — the country’s largest music copyright collective — ended its blanket ban on AI-assisted music and launched a formal registration framework. It will now register works where a human played a substantial role in the writing, composition or arrangement, while purely AI-generated works remain ineligible. That puts an increasingly familiar distinction — AI-assisted versus AI-generated — directly into the rules governing registration and royalties in one of the world’s biggest music markets.

Meanwhile in Europe, new AI Act transparency rules took effect Aug. 2. Providers of generative AI systems must make AI-generated audio, images, video and text detectable in machine-readable form, while certain AI-generated or manipulated content — including deepfakes — must also be visibly disclosed to audiences. Existing systems get until Dec. 2 to meet some of the marking requirements. Violations can carry fines of up to €15 million or 3% of worldwide annual turnover, whichever is higher.

🎧 Song of the Day: “The Fifth Path” by Jestress

This high-energy, angsty track by Jestress is accompanied by a well-developed music video concept: a rejected daughter of Nyx storms the Celestial Court to defend the exiled master who taught her that outsiders don't need permission to become powerful.

💬 Last Word

“When someone says AI is doing ‘most of the work,’ I think we’re measuring the wrong work.”

— AI Music Creator Ron DesJarlais, via LinkedIn

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Copyright 2026 Zinstrel, LLC - All rights reserved

Written by Marcus Lawrence, courtesy of composition platform Versey.ai
Special thanks to our paid subscribers: C.Y. Lee, Daryl Dekking, Lynn Clapp, Steve Clapp, Mete Dibi, Daniel Lares, Dexter Garcia, Matthew Marturano, Sammy Stoltz, Tim Burley, Drew Thurlow, Sheila Spence, Lenny Skolnik, Màuhan Zonoozy, Matti Kuha, and Jacci Cenci-McGrody.

As the music industry scrambles to make sense of AI music — trying to hide it, label it, delete it, or blacklist it outright — the gaps in language and understanding only get clearer. Part of the problem is that “AI music” gets used as a catch-all, and a catch-all creates an instant connotation, even when the reality underneath it is anything but uniform.

Every argument about AI and music makes the same mistake: it treats four distinct economies as one industry, as if they shared a goal, a technology, or a community. They don’t.

Here we’ll discuss these four different economies, who they’re serving, and how they fit into the greater music industry.

These four overlap at the edges. But understanding AI’s role in music starts with figuring out which of the four you’re actually talking about — and right now, most of the industry, and most of the discussion surrounding it, isn’t doing that.

The “AI music” catch-all label isn’t doing anyone any favors.

1. Active Listening: The Industry’s Current Bet

Active Listening is the version of AI music the major labels are most eager to embrace: AI-powered remixing, stem-swapping, voice-cloned fan edits, and other interactive experiences built around music people already know. Spotify, Udio’s upcoming Starstruck app, KLAY Vision, the app suite emerging from A Vinyl Bar in Shibuya, Hook, Starchild, and others are all chasing variations on the same bet — that superfans will pay to remix music they love rather than create something new.

It’s also the version that fits most comfortably inside the existing music business. Artists opt in, rights get licensed, and catalogs stay central. Universal Music Group, Warner Music Group, Sony Music Entertainment, Believe, and Merlin have all signed deals with various platforms to fold their artists into this ecosystem (if they opt in, of course). The enthusiasm in the industry is undeniable and well-documented, because this is an AI music future the industry can underwrite. It doesn’t require surrendering any of its existing structure, it just adds a new monetizable layer on top.

Like we’ve said before about this genre, for all the partnerships and keynote attention, though, Active Listening remains largely unproven. It gets the press releases because it’s the version the industry can most easily imagine controlling — not because anyone’s confirmed that fans actually want it. The real question is still open: will anyone care?

2. Creator Communities: The Economy That Already Exists

The largest AI music population may also be the one the industry fears the most and understands the least. Call them Creator Communities — Suno-native creators building songs, videos, album art, fictional artists, and entire backstories for audiences often measured in hundreds or thousands. Zinstrel encounters creators in these communities on a daily basis. Most have no interest in a record deal, mainstream radio, or acceptance from the conventional music business. They aren’t waiting to break through. They’re building somewhere else entirely, and much of it never touches a traditional DSP. Their motivations aren’t what you might expect.

That doesn’t mean nobody’s making money. A recent Kapwing analysis using Songstats and AiMCharts data estimated the 10 largest AI music acts had collectively generated around $6.1 million from more than 2.3 billion Spotify streams and YouTube views. But breakout viral names like Xania Monet, Solomon Ray, and Breaking Rust aren’t the norm in this space; most of this economy happily lives in Discord servers, Reddit threads, Twitch streams, and Facebook groups, where success looks more like participation and social recognition than chart position.

This community also absorbs the brunt of the industry’s new rules.

With 90.4% of artists in SIQA’s verified Q1 submission pool using Suno, their work is tangled up in that platform’s legal baggage — how much of these songs can even be copyrighted? — on top of a flood of low-effort AI songs hitting DSPs that makes life harder for creators doing genuinely intentional work. It’s why groups like SIQA, the AI Music Creators Association, and AIMRO have emerged: to formally draw a line between artists building real personas and styles, and the stream farmers flooding the market with agentic slop.

3. Hybrid Production: The Biggest Potential

Hybrid Production is the most under-built of the four — and the one where we believe music as a whole is heading. Here, AI is unmistakably a tool in the artist’s hand rather than a replacement for their decisions. It demands real musical skill or taste, yet the tools arriving now are closing the intimidation gap for people who never learned a DAW, without asking them to abandon the production methods musicians already trust. BandLab’s SongStarter, LANDR, and Moises got there first with lighter-touch AI assistance; newer entrants like Riffle and Tamber go further into composition, separation, customization, and arrangement while still leaving the artist in charge of the bigger creative decisions.

This should be the easiest category for the industry to embrace at the cultural level. It preserves human authorship, echoes past waves of production-software adoption, and offers real practical upside without asking listeners to accept a fully synthetic performer. Instead, it remains surprisingly underdeveloped. Mapped against venture taxonomies from the broader AI market — heavy on copilots and workflow tools that extend human capability — the music side of that investment is thin by comparison (although growing). Even live performance and hardware, where human musicians and AI could interact most visibly, barely register, although with hybrid initiatives like Fires of Ardentara and the AI.LOVE.JAZZ contest, that’s changing too.

There’s a second, quieter consequence of that underinvestment: because these tools are built to sit inside a normal production workflow, a song made with them may never carry an “AI” label at all. It’s the same session, just faster — which is exactly why Hybrid Production doesn’t generate the controversy of Suno-driven Creator Communities or the industry affection Active Listening gets. That may be precisely why it’s starved of attention, even though it’s arguably the category best positioned to reconcile “AI-assisted” with “artist-led.”

4. Hidden AI: The ‘Ozempic’ of the Music Industry

Hidden AI use is already running underneath the rest of the business: AI-generated demos, synthetic background vocals, automated production elements, undisclosed voice manipulation, and generative material folded into releases still marketed as fully human-made.

In the demo world, Suno is already replacing work that used to require musicians and studio time, like demos. A songwriter can now generate a convincing version of a finished song before anyone else plays a note. That doesn’t automatically make the final release AI-generated, but it does mean AI is now part of the commercial pipeline, and the industry still has almost no shared language for how much involvement should require disclosure.

Suno CEO Mikey Shulman famously said his platform has become “the Ozempic” of the music industry: everyone’s using it, and nobody’s talking about it.

Notably, the legal and cultural scrutiny keeps landing on Creator Communities, not on what labels themselves are producing — Warner’s lawsuit-ending arrangement with Suno has terms that are unknown to the wider industry. Meanwhile, Warner-owned Spinnin’ Records released The Second Voice’s viral “LET ME BE,” which has topped SIQA’s AI music chart.

The double standard shows up case by case. Fenix Flexin’s “Rubberz” went viral this summer, and despite persistent doubts from producers and fans, our evidence that the song was AI-generated, and Treblo’s own assertions about the song’s origins, Fenix maintains the voice on the track is his. Tyga’s 1980s synth-pop side project track “GAVE U RACKS” has drawn a similar debate. And when Australian DJ Josh Fawaz finally disclosed generative AI vocals and drums on his chart-topping “Like a Prayer” cover — following an investigation and public scrutiny — the song stayed in the country’s Top 5 anyway.

Hidden AI use in the industry doesn’t look like a scandal waiting to happen. Instead, it’s an economy the industry is already living inside without having decided how — or whether — to name it. And unlike Creator Communities, it carries none of the reputational baggage, with all of the convenience.

The Case for Nuance

None of these four economies is going away, and they all solve different problems for different people, with different tools and different stakes.

Collapsing all of that into a single label — “AI music” — isn’t just imprecise, it’s actively unhelpful. There is another phenomenon sitting outside these four creative economies: automated slop farming, where the human effectively disappears from the creative loop. Maybe that is what “AI music” should actually describe.

In all of the aforementioned economies, a human has to be somewhere in the mix. And in all of these, the creators care deeply about what they’re putting out into the world.

Poor labeling lets bad actors hide next to good-faith artists, it lets an untested bet get treated as inevitable, and it lets a genuinely useful category go underfunded because nobody’s arguing about it. Or if they are arguing about it, they’re confusing it with one of the other three.

If the industry, the press, the platforms, and the culture at large want to make good decisions about any of this, they’ll need to be more specific. Say what you mean when you say “AI music.”

🆕 New AI Music Releases

Albums & EPs

• ENZO RITCH – Beautiful Disaster (R&B / Soul)

• Goldie Songs – REGAL (R&B / Soul)

• Leea – Entretenimento (Pop)

• Stored Nerve – Name on my Arm (Rock / Alternative)

Singles

• Dakota Decrypt – “Duality of the Cosmic Collapse” Single (Electronic / Dance)

• Fake Perfection – “Hit Me” Single (Rock / Alternative)

• Gracie – “Unconditionally” Single (Pop)

• Ione – “The TikTok Support Loop” Single (Electronic / Dance)

• Jestress – “The Fifth Path” Single (Hip-Hop / Rap)

• Kojo Osei – “Deadly” Single (Afro-R&B)

• Winther + Dezbal – “CONTROL” Single (Rock / Alternative)

Music Videos

• 1sev7n feat. Jailhouse Lock and From June To December – “The Swarm” Music Video (Electronic / Dance)

🎧 Song of the Day: “Red Flags” by ENZO RITCH

The opening track to ENZO RITCH’s new album, Beautiful Disaster, brings an atmospheric blend of R&B, soul, and hip-hop together.

💬 Last Word

“Every new technology changes the creative process. The people who understand music usually become the ones who use that technology best.”

— Masters Radio Founder Rob Snyder, via LinkedIn

MORE ZINSTREL:
Zinstrel.com | @zinstrel_ai on Instagram | AI Underground on Discord | r/Zinstrel
Copyright 2025-2026 Zinstrel, LLC - All rights reserved

Written by Marcus Lawrence, courtesy of composition platform Versey.ai
Special thanks to our paid subscribers: C.Y. Lee, Daryl Dekking, Lynn Clapp, Steve Clapp, Mete Dibi, Daniel Lares, Dexter Garcia, Matthew Marturano, Sammy Stoltz, Tim Burley, Drew Thurlow, Sheila Spence, Lenny Skolnik, Màuhan Zonoozy, Matti Kuha, and Jacci Cenci-McGrody.

Every Monday night, a Wales-based dark folk artist opens her Twitch channel to music that rarely gets a dedicated stage in the AI music scene: folk, classical, jazz, blues, indie, world music, spoken word, opera and long-form works that run beyond most showcase limits.

The show is called Fires of Ardentara. The person running it is Bridget “Techcowgirl” Aboussafy.

Onstage and off, Aboussafy has spent the last several years confronting a problem much of the AI music conversation overlooks: why musicians using these tools — and musicians who refuse to touch them — still struggle to occupy the same room.

The islands

Moving between different parts of the music world, Aboussafy repeatedly encountered the separation — intentional or not — between different groups of artists.

In Wales, where she lives, Aboussafy has watched musicians settle into circles that rarely overlap: open-mic performers, folk-club regulars, electronic artists and members of the region’s many choirs.

“But they are all islands,” she says.

The metaphor is also how she describes the entire AI music landscape: a scene splintered not just by genre but by a harder, newer line between “organic,” AI-assisted and fully AI-native music, with real hostility running in both directions.

As Techcowgirl, Aboussafy makes historical dark folk that sometimes expands into rock, nu metal and what she calls threshold music. She is classically trained in voice and musical theatre, has spent decades making music and brings a professional technology background to her current work.

She also operates in the space most likely to catch fire from both sides: bringing her own vocals, instrumental snippets, melodies and chord progressions into Suno to develop songs around lyrics she wrote herself.

“As an organic musician, there’s a lot of creative benefit to be had using all the new AI tools at our disposal, in many places throughout our production processes,” she says. “My view is that if people will at least be curious and try it all out for themselves, they will find there was nothing to be afraid of, and they can now much easier get their musical ideas out of their heads and heard by others.”

Crossing between them

Aboussafy’s position is niche within niches. Being a hybrid musician, she says, is genuinely risky in the current climate — and being a historical folk musician on top of it makes it riskier still, since purism runs deep in that world.

She didn’t begin by asking people to enter her room. She spent a year entering theirs.

For roughly a year, Aboussafy made the rounds of mostly AI-focused Twitch and Discord showcases, appearing as a guest or submitting tracks to one host after another. She brought songs built from her own live vocals, instrumental passages, melodies and chord progressions, expanded through Suno and then separated into stems for additional work in her DAW.

At first, she says, people were simply surprised anyone was bridging the gap between pure AI generation and live performance. Then they started liking how it sounded. She kept going and kept bringing more songs until something shifted.

“People are now recognizing my songs by my voice alone,” she says.

At the same time, she brought the same approach into her live band, Celtic Spirit, while developing a new historical concert program. The band had sets of lyrics that needed music and wanted additional songs about regional history. With help from Suno, they worked the lyrics into full arrangements and performed them at the opening concert.

The band was skeptical at first. Watching how quickly they could test different arrangements in rehearsal changed that.

“The audiences who eventually heard the songs didn’t care how they were created,” she says, “only that the songs conveyed the story and emotions contained within them.”

That, more than any verbal argument, is the case she has been building in public for two years. Her work became a proof of concept for hybrid music — repeated until the hybrid part stopped being remarkable.

Building the room

Fires of Ardentara grew from Aboussafy’s realization that hybrid music — and the genres overlooked by AI-focused rock, metal and hip-hop showcases — had no obvious home. The creators making that music were already there, but many were quiet about it.

Across more than a dozen episodes, the show has hosted a spoken-word poet and featured long-form audio stories, short films and test runs of historical documentaries.

Then, in late July, Aboussafy’s worlds collided.

The show recently aired Ardentara’s Acoustic Folk Circle #1, its clearest bridge yet between traditional performance and its wider hybrid community. The live broadcast ran for nearly four hours, creating a dedicated space for the acoustic folk music that had previously sat just outside the show’s established format.

Before the broadcast, the organic musicians Aboussafy invited were curious but cautious — watching to see whether she could make the idea work.

“They want to see if I can do it,” she said, “and if successful they will give it a go.”

The episode has now given them something concrete to assess.

Around the show, Aboussafy has built a wider ecosystem that includes Ardentara at Night and Ardentara Daybreak, ambient and work-focused streams that run for hours at a stretch.

She has also created The Forge Circuit, an opt-in global calendar of creator-led showcases, review streams, listening parties and other music events, built without scraping or reposting anyone’s listings without permission.

Around the calendar, she is developing host and artist interviews, show guides and a standardized anonymous review system intended to help musicians determine whether a particular show is the right fit for their work.

“This way each review is objective, from blind or anonymous observation,” she says, “with the final result being a review that will allow artists to ascertain whether any particular given show is the right fit to confidently present their music at.”

Beyond one show

What makes this more than one artist’s project is that other hosts have started participating, too.

The Forge Circuit now lists a growing roster of independent shows. Hosts have begun running one another’s show-card graphics on screen during their own broadcasts, promoting upcoming programs and attending each other’s shows whenever they can.

The artist-feature format is spreading the same way. Aboussafy and her husband appeared in an artist feature on Lord Starface’s Twitch show early this year, and she says other hosts have since adopted the format themselves.

It is a small step, but a meaningful one to go from getting played, to getting discussed, to eventually performing live.

Her experiment also reflects a broader movement visible at events such as AI.LOVE.JAZZ in Montreux, where a live house band performed AI-composed jazz, soul and funk finalists before an international jury and audience for the first time this July.

This is a different scale with the same fault line: an algorithm creates something fixed, and human performers have to bring it to life in the room.

The next planned expansion is audio-only. Aboussafy says she is developing a station through Live365 that would place AI and hybrid tracks on the radio alongside mainstream artists. She says a first cohort of five hosts and DJs is already on board, with a launch date still being finalized. She expects the first version of that interconnected system to be operating by the end of August 2026.

What it’s all for

Ask Aboussafy what any of this is building toward, long-term, and the answer is not a business plan.

“To bring closer the communities of AI musicians, hybrid musicians, and organic musicians and their audiences,” she says. “The flack I take about even touching AI tools from the old-school organic crowds is intense. This is not how the music communities should be going into the future — the lines need to blur so people can be free to move between and experiment, experience new things. So I figured I’d do my damndest to make that happen.”

The islands are not going anywhere on their own. But in late July, the bridge Aboussafy had spent months describing was finally tested — live, on air, for nearly four hours.

Now the musicians watching from the other side have to decide whether they will cross it.

Techcowgirl hosts Fires of Ardentara Monday nights on Twitch. Find her music on YouTube and Bandcamp, and visit The Forge Circuit at theforgecircuit.com.

💿 SIQA Top AI Songs of the Week

The August 4, 2026 SIQA chart saw its top five tracks remain the same as July 28, while the lower half experienced minor position swaps and welcomed back Yunna Serene's "soft girl era" to the Top 10, coming in at number nine.

🎧 Song of the Day: “The Tide Owns Us All” by Techcowgirl

Get a sense of the blurred genres and epic scale of Bridget Aboussafy’s Celtic hybrid music. Driven by dark folk atmosphere, ritual vocals and hypnotic EDM energy, “The Tide Owns Us All” is an elemental anthem about mortality, fate and the one force that makes no distinction between the powerful and the forgotten.

💬 Last Word

“The next generation of AI platforms isn’t just competing for users. They’re competing for creators.”

— Tallium CCO & AI Creator Christian Schaffner, via LinkedIn

MORE ZINSTREL:
Zinstrel.com | @zinstrel_ai on IG | AI Underground on Discord

Written by Marcus Lawrence, courtesy of composition platform Versey.ai.
I use em dashes proudly.

Special thanks to our paid subscribers: C.Y. Lee, Daryl Dekking, Lynn Clapp, Steve Clapp, Mete Dibi, Daniel Lares, Dexter Garcia, Matthew Marturano, Sammy Stoltz, Tim Burley, Drew Thurlow, Sheila Spence, Lenny Skolnik, Màuhan Zonoozy, Matti Kuha, and Jacci Cenci-McGrody.

Luminate, the entertainment-data firm behind Billboard’s charts, released new AI attitude data July 24, and it reveals a surprising split within Gen Z. Teenagers are more open to AI music, while 18-to-24-year-olds are sharply against it.

Asked how they’d feel learning a song was made with AI, only one age group says they’d actually be more into it: teenagers, 13 to 17, net positive at +19%. Everybody else is net negative — but it’s not a steady slide from “young and open” to “old and closed.”

Listeners 25 to 44 are only mildly turned off, dipping to just -3%. Then 18-to-24-year-olds plunge to -29%. That’s a cliff, and it lands them almost exactly where their grandparents are: 55-to-64-year-olds reported -30%. Two generations, one nearly identical number. Only listeners 65 and older are more skeptical than both, bottoming out at -47%.

So this isn’t young people warming up to AI music while their parents resist. It’s teenagers standing alone as the one genuinely receptive group, with a slice of young adults landing about as cold on AI music as people three decades older.

Labeling may only exacerbate the broader perception problem. MBW shared a recent Stanford/Reed College study that found listeners imagined fewer and less engaging narratives when music was labeled AI, regardless of whether it was actually human- or AI-composed. The reaction tracked the label more than the music itself, helping fuel AI creators’ growing anti-labeling stance.

Gen Z’s broader distaste for AI has been well documented this year: Gallup and the Walton Family Foundation found rising anger and falling excitement, and Pew finds under-30 adults are simultaneously the most AI-exposed and most pessimistic. But a microgeneration actually warming to AI music is noteworthy for the future of the medium amid a sea of pessimism elsewhere.

Google Ships Lyria 3.5 in Flow Music

Google rolled out a new version of its music-generation model, Lyria 3.5, inside its Flow Music app on July 29. The update focuses on four things: richer melodies, better lyrics that actually follow your prompt, more realistic and emotional-sounding vocals (including cleaner pronunciation), and more control over tempo and song length. There’s a whole playlist available for people to listen to what the new model sounds like.

Major Labels Propose AI Chart-Eligibility Rules — With an Unresolved Detection Problem

UMG, Warner, Sony, and eight independents — including HYBE, BMG, Believe, Concord, and Dirty Hit — proposed new rules this week for which AI-involved songs can count on official charts, per Variety. The framework covers authorized AI tools trained on licensed data, copyright and personality-rights compliance, disclosure, and no chart manipulation. The rule doing the heavy lifting remains undefined: a song has to be “substantially human made.”

No chart enforces it yet, Billboard included; it’s just a proposal for now. The bigger problem is that chart compilers generally receive the finished master, not a verifiable record of how it was created. A song with human-written lyrics rendered through AI vocals may be difficult to distinguish from one involving far less human authorship. Under these rules, songs could be treated as fully AI-generated and disqualified despite meaningful human input.

Suno Adds Text-Prompted Cover Art Editing

Suno now lets you upload an image on web and edit it just by typing what you want changed — you can generate either a new still image or a short video out of it. It works across song covers, playlists, and your profile picture and banner. It continues Suno’s push to build out the whole visual side of an artist’s presence on the platform.

Treblo Confirms: “RUBBERZ” Was AI Generated

AI music platform Treblo released an open-source classifier on Aug. 3 that detects whether a song was generated on its own platform, claiming a false positive rate below 1 in 10,000.

Additionally, co-founder Ryan Tremblay officially confirmed what Zinstrel and AI detection firm HumanStandard reported back in June: Fenix Flexin’s hit summer song, “RUBBERZ,” was created with Treblo.

“We built Treblo for everyone, from normal people experimenting at home to charting artists looking for new sounds,” he said. “Someone appears to have used our model to find a sound that millions of people connected with and that’s exciting.”

The classifier currently only detects Treblo’s own models. The company says it’s working to extend coverage to other major platforms.

With this confirmation, Tremblay says “RUBBERZ” becomes the first known AI-generated song to reach the Billboard Hot 100. It also contradicts the repeated denials the Shoreline Mafia member has made regarding the song’s AI use.

Treblo shared three links alongside the announcement. A blog post at treblo.com/blog/treblo-ai-music-classifier lays out the company’s rationale and results. A web classifier at treblo.com/detect lets anyone upload or link a song and get a probability score for whether it was made on Treblo — no account or technical background required. And an open-source repo at github.com/Sonauto/treblo-classifier makes the underlying model available to developers, researchers, or competing platforms who want to run it themselves or build on it.

The news lands as scrutiny of “RUBBERZ” is already resurfacing. Seven of the 15 dates on Fenix Flexin’s tour — Seattle, Sacramento, San Diego, Santa Ana, Los Angeles, Tucson, and Brooklyn — are now marked “Cancelled,” with no explanation given. The cancellations follow a viral video from creator medasin, “The Reckoning of Fenix Flexin & Purps,” that’s put the AI allegations in front of a much bigger audience.

Fenix Flexin’s public stance has also shifted since June: rather than denying AI involvement outright, he’s now saying only that he “never lied.”

Mureka Adds Sheet Music Export for Generated Songs

Mureka launched a new feature in its Editor suite called Download Score that turns your AI-generated song into actual sheet music with chords, right inside its editor. Mureka’s pitching it for a few uses: playing your song on a real instrument, pulling the chords into a DAW to keep producing, studying the song’s structure, or using it for collaboration and copyright registration. That last one is the interesting part — notated sheet music may make a song easier to document and submit, but it doesn’t resolve whether the underlying AI-generated composition qualifies for copyright protection.

CHRT Music Launches as a Chart Built Only for AI-Generated Songs

While major labels are trying to get AI songs banned from official charts, the AI music world continues to try to develop its own charts. A new platform called CHRT Music just launched, and it only ranks AI-generated songs. It runs on three-week “seasons” that overlap on purpose, so a new submission window opens the moment the last one closes, and ranking is based on verified human plays rather than judges. Creators earn permanent badges as they hit certain play-count milestones, and whoever tops a season gets a spot in CHRT’s Hall of Fame. Free accounts get five submissions a month; paying unlocks unlimited. CHRT is stepping into territory already covered by SIQA and UpChart, but leaning into the certification and season format as its angle.

🎧 Song of the Day: “WiggityWippity-DopBopShoWop-SugarCoat-SweetTalk-SodaPopDrop” by Duchess of the Damned

Mobvision, a Discord-run AI music contest, crowned its third-edition winner last week: Chilean producer Kaiman, for his earworm track “WiggityWippity-DopBopShoWop-SugarCoat-SweetTalk-SodaPopDrop” by his virtual project, Duchess of the Damned.

💬 Last Word

“Unless a legacy corporation controls your creativity and profits from your revenue, your work has no recognized value and is barred from free and fair access to fans.”

— Mark Grissom, owner and music publisher at Grissom Music Group, announcing a new AI advocacy group, the Association of AI-Assisted Creators & Fans

MORE ZINSTREL:
Zinstrel.com | @zinstrel_ai on IG | AI Underground on Discord
Copyright 2026 Zinstrel, LLC - All rights reserved

Written by Marcus Lawrence, courtesy of composition platform Versey.ai
Special thanks to our paid subscribers: C.Y. Lee, Daryl Dekking, Lynn Clapp, Steve Clapp, Mete Dibi, Daniel Lares, Dexter Garcia, Matthew Marturano, Sammy Stoltz, Tim Burley, Drew Thurlow, Sheila Spence, Lenny Skolnik, Màuhan Zonoozy, Matti Kuha, and Jacci Cenci-McGrody.

A Munich court ruled Friday that Suno infringed copyright in a case involving six musical works, finding that the compositions were reproducibly contained in the company’s v3.5 and v4 models and recognizable in generated outputs.

The court largely granted GEMA’s requests for an injunction, disclosure and damages, with the amount to be determined later.

GEMA is the German collecting society representing more than 100,000 composers, lyricists and music publishers. Its lawyers demonstrated that Suno could generate substantially similar versions of “Rasputin,” “Daddy Cool,” “Mambo No. 5,” “Forever Young,” “Big in Japan” and “Atemlos durch die Nacht” without being given instructions about their melodies, harmonies, rhythms or arrangements.

The court concluded that the works had been memorized: training material could be contained within an AI model and extracted through its outputs. It also found that Suno had included the six works in its training dataset after extracting them from YouTube through stream-ripping techniques that circumvented the platform’s rolling cipher.

Suno faces several other high-profile lawsuits, but GEMA’s is the first case against the company to reach a judgment.

Takeaway 1: Suno’s problems go far beyond its training data now

What makes this ruling dangerous for Suno isn’t just the underlying training question, it’s how easily the infringement was proven. GEMA’s legal team didn’t need to hack anything or reverse-engineer the model. They opened Suno’s ordinary prompt box — the same one every paying subscriber uses — typed in the original lyrics, a style description, and a song title, and got back a version of “Rasputin” close enough that the court ruled out coincidence given the complexity and length of the material. That’s the same result for “Daddy Cool,” “Mambo No. 5,” and six works in total.

The financial exposure is still unclear, and that’s arguably the scarier part for Suno. The court hasn’t set a damages figure — that comes after the disclosure phase, where Suno has to open its books on revenue tied to the infringing outputs.

Suno was valued at $5.4 billion in a June funding round. GEMA’s CEO called it “a verdict of global significance,” and the scale of the exposure — plus what disclosure reveals about how much of Suno’s revenue this touches — will shape how aggressively UMG and Sony pursue their own claims.

Takeaway 2: This cuts to the heart of Suno’s promise

For two years, Suno’s entire pitch rested on one distinction: the model doesn’t copy, it creates. Feed it a prompt, and what comes back is new — inspired by the corpus, not lifted from it. That distinction is what let Suno tell courts, labels, and its own users that this was a creativity tool, not a laundering operation.

Friday’s ruling seriously weakened that claim. The court did not hold that every act of AI music training is inherently illegal. It held that these six works had not merely influenced the model in some abstract sense: protected elements were reproducibly contained in v3.5 and v4 and emerged in substantially similar outputs without the prompts specifying their melodies, harmonies, rhythms or arrangements.

That is the difference between “this sounds influenced by ‘Rasputin’” and “this reproduces protected elements of ‘Rasputin’ closely enough to infringe.”

Takeaway 3: Suno users should demand answers

There’s an implication here that has nothing to do with UMG, Sony, or appellate courts, and everything to do with the people actually using Suno to make music. The court found that six copyrighted compositions could be reproduced from two widely used Suno models — v3.5 and v4 — through the same kind of interface available to ordinary users.

That creates a serious product-trust problem rather than just a legal one. Six adjudicated songs don’t prove widespread memorization across every Suno model, but they do make blanket assurances of originality much harder to accept without more testing and transparency.

If protected elements were reproducibly contained in v3.5 and v4, users have reason to ask what safeguards Suno employs before presenting its outputs as original and commercially usable.

At minimum, that complicates what Suno creators think they have made: their prompts may sometimes be drawing from memorized compositions rather than shaping something genuinely new. The court placed legal responsibility for the six infringing outputs on Suno, but the uncertainty surrounding other outputs remains a problem its users deserve answers about.

Takeaway 4: Its effect on the US cases remains to be seen

The ruling is not a verdict against Suno in the UMG and Sony lawsuits, which are separate cases, in a different country, under different law, before different judges. Nothing about Friday’s decision binds a US court, and Munich’s reasoning on the American fair-use test carries no legal weight in Massachusetts — a German court doesn’t get to decide what 17 U.S.C. § 107 means, however pointedly it argued that “the copies are not covered by the fair use doctrine... as applicable in US law” and that the Warhol factors all cut against Suno.

But that said, it is a fully worked-out template for the exact factual argument UMG and Sony need to win their own cases, tested for months against real evidence. It hands their lawyers a domain-tested version of the memorization argument, plus a pointed distinction from the Anthropic and Meta book rulings that undercuts the precedent Suno was likely counting on.

That is persuasive material, not binding precedent, and the Massachusetts case will not test its influence immediately. Under the current schedule, dispositive motions are not due until April 9, 2027, making any US fair-use ruling a 2027 event at the earliest.

Takeaway 5: This isn’t over

Friday’s ruling is not yet final, in the sense Suno can appeal to the Oberlandesgericht München. “We disagree with today’s ruling... and are evaluating all available options, including an appeal,” reads a statement from Suno. So it looks like it’s headed that way.

This is also the second consecutive Munich ruling against an AI company built on the same memorization framework, following November’s OpenAI decision on song lyrics. OpenAI’s appeal of that ruling is already sitting at the same appellate court, which means Oberlandesgericht München could end up reviewing both cases in separate appeals — and begin defining how durable the Munich court’s approach will be.

🆕 New AI Music Releases

Singles

• Garbage Garden – “emaN yM yaS” (Electronic / Dance)

• J.vito – “You’re Not Alone” (Liquid Drum-and-Bass/Dubstep)

• Kojo Osei – “Dear Father” (Afro-Soul)

• SYRA_404 – “The Glass Handshake” (Electronic / Dance)

• Zara Blue – “The Birthmark” (R&B / Soul)

Music Videos

• Rizzards – “Necromancer” (Electronic / Dance)

• Roy Thigpen – “Diving in” (R&B / Soul)

🎧 Song of the Day: “The Glass Handshake” by SYRA_404

Blending hard-edged jungle beats with a chill yet dark and moody atmosphere, "Glass Handshake" delivers a driving rhythm that invites you to meet in the middle and sink into its noteworthy, atmospheric groove.

💬 Last Word

“I'm forty years in and I'm not worried about the tools. I'm worried about composers who mistake speed for skill, and who won't understand what they lost until the market corrects.”

— TV/Film music producer Hans York, via LinkedIn

MORE ZINSTREL:
Zinstrel.com | @zinstrel_ai on Instagram | AI Underground on Discord | r/Zinstrel
Copyright 2025-2026 Zinstrel, LLC - All rights reserved

Written by Marcus Lawrence, courtesy of composition platform Versey.ai
Special thanks to our paid subscribers: C.Y. Lee, Daryl Dekking, Lynn Clapp, Steve Clapp, Mete Dibi, Daniel Lares, Dexter Garcia, Matthew Marturano, Sammy Stoltz, Tim Burley, Drew Thurlow, Sheila Spence, Lenny Skolnik, Màuhan Zonoozy, Matti Kuha, and Jacci Cenci-McGrody.

Congress is moving on the NO FAKES Act. Major music-industry organizations, including the RIAA, have introduced a new labeling standard for distinguishing generative AI in sound recordings. Deezer is starting to delete AI music that doesn’t get plays, while TIDAL has started denying royalties to music it classifies as wholly machine-made. Artists also say Spotify is changing how it handles AI music.

Each decision will help determine how AI music creators can distribute, label and earn from their work. None appears to have been made with an AI music creator in the room.

That’s the gap a new membership association wants to close. The AI Music Creators Association (AIMCA) launched this month with a straightforward pitch: while everyone else fights over what to do about AI music, someone should be organizing the people actually making it.

What AIMCA is Building

AIMCA launched on July 25, 2026 as a membership association for anyone who makes music with AI — casual prompters, hobbyists, independent artists, producers, prompt designers, educators. Its founding charter is direct about the goal: “to represent, support, and advance the interests of AI music creators worldwide,” so they “have a seat at the table” as the technology reshapes who gets to make music.

AIMCA is led by Executive Director Mary Devlin, with her husband, UPCHART founder and CEO Mark Devlin, serving as co-founder.

Mary Devlin is a longtime entrepreneur and marketing professional, not a music-industry figure. That marketing and public-relations background shaped how she approached what she saw as a massive unmet need.

“I saw an incredible community of people creating music with AI... who are being told their work isn’t ‘real’ creativity or that it has no value,” she said, describing what pushed her to start the group. “It is shocking how these ordinary people have been unfairly portrayed in a negative light, by entrenched interests, and have had no way to speak back.”

AIMCA’s advocacy reads like a direct response to the news cycle above. It opposes blanket AI labels — “warning stickers and stigma help nobody, and punish creators” — and platforms that “still treat AI-assisted music as second-class.” It wants “clear, fair royalty pathways” instead of creators being treated “as an edge case,” and the right to download and keep their own work without “rent extracted by companies that did not write, perform, or produce the music.”

Its plan for getting there is fairly conventional: lobbying, research, education, community-building, and industry recognition.

It’s not the only organization pursuing AI music advocacy — the Sonic Intelligence Academy (SIQA) and the AI Music Rights Organization (AIMRO) pursue some overlapping goals — but AIMCA is going all-in on volume: signing up individual members by the thousands rather than working the policy circuit alone.

“The larger our membership, the stronger our collective voice becomes,” Devlin says.

Associate Membership is free and non-voting; Founding Membership runs $10 a year and comes with a vote on AIMCA’s priorities and representation. There are also memberships geared towards music industry and media organizations.

The ideal AIMCA member, Devlin says, is broad. “It’s for anyone who creates music using AI. That includes casual prompters, hobbyists making songs for fun, independent artists building audiences, professional musicians using AI as part of their creative process, producers, prompt designers, educators and people building careers around AI music.”

Asked why anyone should listen to an association competing for consideration alongside entrenched labels and publishers, Devlin doesn’t concede the competition.

“We’re not trying to compete with traditional music industry groups,” she said. “Our job is simply to represent potentially millions of AI music creators, because nobody else is doing that.”

Turning a Scene Into a Constituency

Devlin says the early response to AIMCA has surprised her.

“We’ve had messages from creators saying, ‘It’s about time someone did this.’”

The handful of artists currently listed by AIMCA as members defy the stereotypes surrounding the people behind AI music. They have small, committed followings, haven’t yet gone viral, and aren’t making money from their music. Their participation looks less like a quick attempt to game the system than a sincere investment in making and sharing work.

One of those early joiners is Terje William Dahl, who releases music as William Cloudborn. He says he joined AIMCA as a Founding Member because the public conversation about AI music keeps collapsing into two extremes: it’s either soulless, fraudulent rubbish, or it’ll “magically democratize everything.”

What he wants AIMCA to accomplish is less a defense of AI music than a reframing of the conversation. He’d rather the debate move past whether AI music is “real” and toward whether it was created honestly, and whether the rules are fair to both existing artists and new creators.

“We should not be discussed only as a technical problem, a copyright threat or a category of content to be labelled and hidden,” he says. “We should also be recognized as human beings using new technology to communicate.”

He also wants the industry to become more precise about how it discusses AI music.

“I hope it helps distinguish sincere creative work from impersonation, mass-produced spam and deliberately deceptive content,” he says. “Those things should not all be placed in the same box.”

But above all, he says, “I hope AIMCA gives people a seat at the table who would otherwise only be spoken about, rather than spoken with.”

The Urgency of the Moment

None of the activity in that opening list is slow-moving or theoretical. Congress, major music-industry organizations and three DSPs are all advancing rules, standards or platform policies that could determine how AI music is labeled, distributed and monetized. Those decisions are being shaped in rooms where the closest thing to an AI creator advocate may be a platform’s own community team.

As things change quickly, the Devlins sense the urgency of the moment. Although they aren’t starting from a massive base of reach, they do have one built-in constituency.

The pair runs UPCHART, an AI music discovery platform that’s home to more than 1,200 creators and around 3,800 songs as of this week. The bet is that a meaningful share of them can become the foundation of an advocacy base. Although that connection gives AIMCA an immediate recruitment pool, it also means the organization will eventually need to demonstrate that it represents a broader creator community rather than primarily the users surrounding one platform.

AIMCA is very new. Its publicly listed membership is still small. But the ambition is undeniably big.

Whether AIMCA becomes a real counterweight to the current wave of labeling and licensing decisions will depend on its ability to grow its membership, unite creators with very different goals and get into the right rooms. For now, that influence remains theoretical.

The association hasn’t yet faced its first real test: a labeling fight, a platform policy reversal or a legislative hearing where it must represent the membership it has assembled.

But the gap it is naming is real: no existing organization has yet assembled a broad, visible constituency capable of showing up when governments, labels and platforms decide what an AI music creator’s work is worth — and representing what the people making it actually think.

💿 SIQA Top AI Songs of the Week

This week’s charts shows the continued dominance of The Second Voice, M.Sasuke, Oliva B Moore and Thompsxn Therapy.

🎧 Song of the Day: “Coconut Skin” by Zuri Usiku

More and more viral videos are starting to feature the latest Afrobeat contender to climb the SIQA charts. Zuri Usiku’s smooth, sexy “Coconut Skin” sits at No. 10 and offers an ideal midsummer sexy head-nodder.

💬 Last Word

“Over 100 million people have used AI generation tools to make music. Anyone who thinks that’s not ‘the music industry’ is just clinging to the industry they wish still existed. Move on.”

— UPCHART Co-Founder/CEO and AIMCA Co-Founder Mark Devlin, via LinkedIn

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Written by Marcus Lawrence, courtesy of composition platform Versey.ai.
I use em dashes proudly.

Special thanks to our paid subscribers: C.Y. Lee, Daryl Dekking, Lynn Clapp, Steve Clapp, Mete Dibi, Daniel Lares, Dexter Garcia, Matthew Marturano, Sammy Stoltz, Tim Burley, Drew Thurlow, Sheila Spence, Lenny Skolnik, Màuhan Zonoozy, Matti Kuha, and Jacci Cenci-McGrody.

A federal judge gave final approval on July 20 to Anthropic’s $1.5 billion settlement with authors and publishers — approximately $3,000 per book across roughly 482,000 works. It is the largest copyright class-action settlement in US history, per Reuters.

Judge William Alsup ruled that using books to train Anthropic’s models qualified as fair use, but downloading pirated copies and retaining them in a permanent central library did not. That left Anthropic facing a jury trial over damages tied to those copies. After Alsup retired, Judge Araceli Martínez-Olguín gave the agreement final approval.

That settlement lands differently for Suno this week. The same day, July 20, Have I Been Pwned reported that a November 2025 breach affected 55.3 million unique email addresses. The stolen data also included names, phone numbers, physical addresses, purchase records and, in some records, partial payment-card details. The incident was first exposed by 404 Media and had not been disclosed to Suno users.

The leaked material also included Suno source code that reportedly showed the company scraping music and lyrics from YouTube Music, Deezer and Genius for model training.

Alsup’s ruling does not bind the judges overseeing the record-label lawsuits against Suno and Udio, and Anthropic’s settlement prevented an appeals court from reviewing it. But it offers a clear warning: one federal judge treated training as fair use while leaving piracy-based acquisition exposed. If plaintiffs can authenticate the leaked code and persuade the court to admit it, it could become significant evidence of how Suno acquired its training data.

BandLab Technologies Acquires Aiode

BandLab Technologies has acquired Aiode, an AI-powered digital music studio built around audio-to-audio models trained with professional session musicians and producers. The deal gives BandLab a third music-making platform alongside BandLab and Cakewalk, with Aiode positioned as the AI-native member of the family. Aiode says all of its training audio is licensed and traceable to source, and its musician-based models are built in collaboration with the musicians themselves. The move continues a run of recent acquisitions for BandLab Technologies — Cakewalk, ReverbNation, Airbit — and builds on its existing relationship with Universal Music Group. According to the Sonic Intelligence Academy’s Q1 Data Report, BandLab was the second-most-used platform within its AI creator submission pool, behind Suno.

Music Industry Groups Agree on AI Labeling

IFPI, RIAA, A2IM, WIN, IMPALA, The Grammys, SAG-AFTRA, and the Human Artistry Campaign announced a joint standard distinguishing “AI-Generated” (primarily made with AI) from “AI-Assisted” tracks (deploying AI for some elements), complete with suggested icons and metadata support — though the system doesn’t yet extend to lyrics, composition, video, or cover art. The organizations are now seeking adoption by streaming services, distributors and aggregators. Labeling continues to be the subject of great debate in the AI music conversation, and we had contributors sharing their reasons for labels and against them via Zinstrel last week.

AI Music Creators Association Launches

UpChart Founder/CEO Mark Devlin has launched the AI Music Creators Association (AIMCA), a new advocacy group built to specifically represent AI music creators. Its stated mission opposes what it calls discriminatory labeling and unnecessary barriers to AI music, seeking to be a direct counterweight by promoting “fair policy and creative freedom” for all artists. The AIMCA is accepting new members, with membership tiers running free for non-voting members and €12 for founding (voting) members. Stay tuned to Zinstrel for more information about this.

GEMA Launches PLAI

GEMA — a powerful German performance rights organization and collecting society — has launched PLAI, a licensed music dataset for AI training built from more than 178,000 audio files from roughly 57,000 works across 60-plus genres, with audio-transcription company Klangio as its first user. The pitch is straightforward: rights, master recordings, audio, and metadata all cleared from one place — positioned as the “no more excuses” alternative to scraping for any AI company building music tools. Although every contributing rights holder is paid from PLAI licensing fees, the exact structure hasn’t been made public.

Josh Fawaz’s AI Madonna Cover Draws Scrutiny

According to ABC News, Australian DJ Josh Fawaz added AI credits to his chart-topping Madonna cover “Like a Prayer” following an investigation and mounting scrutiny over how it was made. The track had led Australia’s national airplay chart for four weeks before Fawaz added credits for generative AI vocals and AI drums on Spotify. He later shared a video demonstrating his creative process using Suno. The controversy has become a real-world flashpoint for the labeling debate playing out across the rest of this week’s news.

Product/Feature Updates

• ElevenMusic added two new features — Vocals and References — to its platform, letting creators generate songs with a consistent AI voice from uploaded recordings or steer generations using a reference track, across ElevenMusic, ElevenCreative, and ElevenAPI.

• Treblo — the growing AI music platform suspected to be behind the Fenix Flexin hit, “RUBBERZ” — launched its mobile app on iOS and Android after completing its open beta.

• Suno has unveiled integration with iMessage, letting users create and send AI songs as message extensions (iOS only).

• Google Flow Music announced it has updated Spaces to support song generation and editing, stem splitting, and image, lyric, and video generation. Plus, instrumental uploads are now live for remixing.

• Mirelo — the platform that generates custom sound effects, foley, and music for visual media — released an API for its Audio-to-MIDI model, following last week’s release of the open-source MuScriptor transcription models.

• Baby Audio — the independent maker of creative audio plugins — released SubCulture, a plugin that listens to your track in real time and adds deep, adaptive bass beneath it, tracking pitch down to 45Hz so the low end always matches what’s playing.

Community News

• AI.LOVE.JAZZ announced its inaugural Montreux winners, with “Frozen Edge” by Dr. Dragon (South Korea) taking first place. Learn more about the groundbreaking event in our recent Culture piece.

• ElevenMusic’s “Summer of Sound” event has launched, increasing free generations to 400 a month and offering $50,000 in prize money for the ten most-streamed tracks on the platform through Sept. 1.

• AI music pioneer Xania Monet (and her creator, Telisha “Nikki” Jones) marked one year since the artist’s debut with a joint Instagram post teasing a new album, “REDEMPTION.”

• The Astana AI Film Festival opened submissions for its first edition, offering a $1 million prize pool for an October 1–3 event in Kazakhstan. That’s the largest prize pool yet for AI-native cinema. Entries are accepted through Aug. 15.

• The AI music Discord community AI Umbrella has relaunched as Viibr Music with a major community update: voice-channel streaming, a redesigned website, synced lyrics, curator tools, and a new “Track Swap” contest format.

• Chat-based AI music generator Tunesona is shutting down without explanation after less than a year in operation. The platform is giving users a window to save their songs before the service closes. Some prepaid “lifetime” plan holders have taken to Discord to express their displeasure, calling the closure a scam and casually floating legal action.

🎧 Song of the Day: “Litany of the Unseen” by Atavic Ark

“Litany of the Unseen” is the first track of the concept album by Atavic Ark that follows the journey of Priestess Azora through twelve primordial gates.
The electric guitar serves as the living mirror of her soul, mutating in real time with every confrontation. The album traces a ritual Nordic folk amplified into sludge, doom, and space rock psychedelia.

💬 Last Word

“Not everything needs to become a career. Not everything needs to be a side hustle or a desperate attempt to disrupt the industry or build passive income or grow an audience or hack an algorithm. Adults are still allowed to play.”

— Mark Lemuel, music producer and sound engineer at Santelmo, via LinkedIn

MORE ZINSTREL:
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Copyright 2026 Zinstrel, LLC - All rights reserved

Written by Marcus Lawrence, courtesy of composition platform Versey.ai
Special thanks to our paid subscribers: C.Y. Lee, Daryl Dekking, Lynn Clapp, Steve Clapp, Mete Dibi, Daniel Lares, Dexter Garcia, Matthew Marturano, Sammy Stoltz, Tim Burley, Drew Thurlow, Sheila Spence, Lenny Skolnik, Màuhan Zonoozy, Matti Kuha, and Jacci Cenci-McGrody.

The biggest misconception people have about Deezer’s AI music policy is that it is anti-AI music.

That’s what the music streamer’s Chief Innovation Officer, Aurélien Hérault, tells Zinstrel.

A passive observer could be forgiven for thinking otherwise. Despite having just 3.1% of Spotify's paid subscriber base, Deezer has become the industry's leader in AI music detection. It was the first DSP to add AI labels to songs, first to keep such music out of algorithmic recommendations.

On the verge of Deezer’s latest report — which attests that more than 50% of new music uploads are now AI-generated — I went to Deezer’s Paris headquarters to find out why so much of the company’s energy goes toward AI detection, labeling, and catalog management.

In the process, I uncovered some unexpected nuance.

Why Deezer Got Into AI Detection

Deezer built its detection system in-house starting in early 2025, to answer a question nobody in the industry could: how much of the “official,” licensed side of streaming was actually AI-generated. Once detection began, the numbers proved what Deezer suspected: massive amounts of AI-generated music flooding the platform. The numbers kept climbing: 28% of uploads in September 2025, 44% by April 2026, and as of the company’s July 21 report, more than half.

“We consider this not only a Deezer problem, it’s an industry problem,” Hérault said. “It’s our position to open our technology to others, if they want to follow Deezer.”

To that end, Deezer has licensed that detection technology to labels, distributors, and rights organizations since January. It’s now the tool Billboard uses to audit its charts.

What the tool is actually hunting for isn’t AI music in a blanket sense — it’s the fraud riding on top of it, Hérault says. Deezer reports that up to 85% of streams on fully AI-generated tracks in 2025 were fraudulent. That’s massive compared to an 8% fraud rate platform-wide.

Hérault’s own language keeps circling back to that target. “What we are against is spamming, and trying to capture royalties from real artists,” he said.

What Counts as AI Music?

Deezer’s tool identifies artifacts specific generative models leave behind in audio — invisible to a listener, but detectable in the signal, which also lets Deezer identify which model produced a track.

Tagging happens at the album level, so one AI track doesn’t tag an artist’s whole release if they have a substantial non-AI catalog elsewhere. A track only gets flagged if it’s either fully AI-generated or delivered at volume.

The criteria are entirely output-based, and that creates a sharp divide between what it considers human-made versus AI-generated. I asked Hérault directly: “If I hum a melody I wrote and write my own lyrics, but Suno generates the finished song from that input, does it count as fully AI?

“Yes, it would be fully AI, because it’s the output of the tool,” he said. The origin of the musical creation doesn’t factor in — only whether the platform, not the artist, produced the final recording.

Hybrid work is treated differently. A track built from an AI-generated stem, folded into an artist’s own composition, isn’t flagged at all. Hérault called it “an artistic usage,” and expects it to become standard as generative tools get built directly into the software musicians already use.

“We’re starting to arrive in a time where there is a lot of hybrid music from musicians— between AI and real composition,” he said. “And for us, that’s OK.”

He also sees a split coming that Deezer hasn’t built policy around yet: right now, a track counts as fully AI regardless of which tool made it, licensed or not. He expects that to change, allowing for nuance between models built with licensed training data — what he calls “legal” models — and “illegal” models, whose training data is in dispute.

“At one point I think we will have two levels,” he said. “One would be clear and clean, so we will probably not flag it as AI-generated content, because they have rights to do it.” The “illegal” side of that future split is exactly where Suno and similar platforms sit today.

The Consequences of the AI Label

The AI label, however, leaves no room for effort or craft. Kara Vale’s Heaven.exe — a nine-month labor of songwriting, prompting, and chopping stems in Suno Studio — gets treated the same as a 30-second agentic slop-farm generation.

Hérault didn’t dispute that.

“Today it’s a big question,” he said, “because musicians do spend a lot of time creating music with this kind of tool.”

But he was clear the actual consequence of receiving the AI tag is smaller than people assume. A flagged track isn’t removed, isn’t blocked, and is paid the same royalty rate as anything else.

“There’s no difference in how these artists get paid,” he said. “The only difference is that when something is flagged, it’s not included in the algorithmic recommendations.”

Deezer can also reverse a flag if it later finds evidence a track shouldn’t have been tagged.

As part of the July 21 announcement, Deezer said it will now “systematically take down AI-tracks used for streaming fraud, and those that haven’t been streamed for at least 6 months.”

Besides eliminating fraud, the reasoning ties back to a cost most listeners never think about: storage. In June 2026 alone, Deezer saw a daily average of 90,000 AI-generated songs uploaded to its servers. All the while, those songs account for only a small fraction of streams on Deezer, between 1-3%.

“What do we do with all this content that we pay to store, that nobody is using or listening to?” Hérault asked.

The listening data backs it up — human music stays stable, he said, while AI content keeps climbing without the plays to match.

Deezer’s Monetization Reality vs. Tidal’s

Tidal made news in early July by cutting off monetization entirely for fully AI-generated content. Deezer hasn’t done that, though Hérault didn’t fully rule it out.

“Labels and the industry are talking about demonetization,” he said. “Today we are not there, but it’s under discussion.” What Deezer is more seriously considering is a volume-based fee — $0 for a single album, but real cost for anyone flooding the platform with hundreds of songs a day.

Deezer can afford to hold that line because of how it already pays artists — differently from the industry standard. Most platforms, including Spotify, pool all subscriber money and pay it out by total plays platform-wide. This “pro rata” model means a fraudulent account streaming one artist thousands of times siphons real money out of everyone else’s share.

Deezer instead caps each listener’s contribution at 500 streams a month, so a listener’s fee only ever splits among the artists in their own plays — simpler numbers, and it dismantles that fraud math directly, since streaming past the cap adds nothing to the pool worth siphoning.

The eventual goal, per Hérault, is going fully user-centric: money following only the artists a listener actually plays. “It’s fair, and it’s transparent,” he said — and it dramatically reduces the incentive for stream farming.

That system wouldn’t carve out AI music as its own category. An artist working with Suno, flagged and excluded from recommendations, still gets paid exactly the same way the moment a listener seeks them out directly.

“You know where your money goes,” Hérault said. “It’s the choice of the user.”

That’s the real distinction from Tidal; Deezer isn’t shutting AI artists out of the money — it’s just refusing to actively promote them.

The Future of Music with AI

None of this makes Deezer anti-AI. Hérault thinks AI will fade into the background of music-making the way Autotune and sampling did, expects licensed models to eventually get treated differently than unlicensed ones, and already has a payment system built to route money to AI artists the moment a listener seeks them out. Fraud is genuinely the target here, not a talking point.

But go back to the artists who spend many months creating within Suno’s ecosystem. Nothing here changes their situation. It’s still flagged the same as a twenty-second prompt, still excluded from the recommendations that would put it in front of new listeners, and still sorted by output rather than effort. Deezer has built a coherent system for catching fraud at scale. It hasn’t built one that knows the difference between a shortcut and a craft. And it’s not too concerned about that.

Every carve-out in Deezer’s policy — the hybrid exemption, the album-level tagging — is built around hybrid work, not fully-generated outputs. The 28-to-44-to-50%-plus growth curve looks, on its face, like fully generated music is taking over. But that volume is exactly what Deezer treats as noise — fraud, bot farms, mass delivery its own numbers show almost nobody listens to.

Strip that out, and Deezer’s real bet is narrower: the durable future of AI in music looks like an artist creating with a fully licensed model — rather than a scraped or disputed model. It looks like a former prompt jockey using a new tool to help them play their own notes over an AI-generated bass line. Or an artist training an AI model on their own catalog to generate new songs powered by their creative consciousness. It doesn’t look like a slop farm’s four-hundredth upload this week.

Deezer isn't betting against AI music. It's betting that the future belongs to artists who use AI — rather than factories that mass-produce it.

Editor’s Note

I’m back! I wanted to take a moment to thank my guest columnists for the past couple of weeks. I thoroughly enjoyed handing over the mic to some knowledgeable, invested professionals whose viewpoints — some of which opposed one another — really added to the AI music conversation.

• Steve Stewart, AIMRO (7/13): “Human Creators Are Powering AI Music. They Need to Get Paid.”

• Itai Leibowitz, Vibya (7/15 & 17): “What ‘Made With AI’ Actually Warns You About” and “When AI Transparency Becomes a Penalty”

• Rasha Rahman, HumanStandard (7/20): “Why AI Music Detection Helps AI Creators”

• Mark Devlin, UpChart (7/22): “AI Music May Be the Most Human Music of All”

🆕 New AI Music Releases

It’s a big list today, as we are catching up from time off. There are lots of new songs, albums, and videos to enjoy from the past couple of weeks.

• Atavic Ark – “The 12 Gates” (Ambient Ritual & Electric Guitar)

• Cassia Voss – Fractured: Before the Fall and Fractured: On the Way Down (Electronic / Dance)

• Detritions – The Red Gate (Rock / Alternative)

• Frank Dezbal – “Battlefield” Single (Rock / Alternative)

• Furbifier – The Surface (Rock / Alternative)

• Ginger Rocazzo – “Black Cat” Single (Rock / Alternative)

• Ione – “Arcane Sovereign” Music Video (Rock / Alternative) and “Dribble Dreams” Music Video (Pop)

• J.vito – “Cold Pressure” Single (R&B / Soul)

• K Λ I – “I Thrive” Music Video (Pop)

• Kirelli – “Hide ‘N Seek” Single and “My Imagination” Single (Electronic / Dance)

• Left-Handed Luminary – Digital Humanity: Chasing Sparks (Electronic / Dance)

• Lily Linda – “All the Way” Single (R&B / Soul)

• SarabiXp – “OUTRISE” Single (Emo / Metalcore)

• Shadrix – Anomaly (Experimental r&b & hiphop with electronic elements)

• Shoes For Louie – Beautifully Unwell (Rock / Alternative)

• Slime Dot – “Up Again” Single (R&B / Soul)

• Solène – “Somewhere Between You and I” Single (Electronic / Dance)

• Stereo Royale – “Little Yellow Bird” Single (Pop)

• stevieskyline – Stages (Rock / Alternative)

• Subroutine Dream – Lazy Expensive (R&B / Soul)

• VANYRA X – “Perfect” Single (Pop)

• Violet Hart & The Riots – Every Face I Meet (Rock / Alternative)

• Wyatt Mercer – “Hotter Than July” Single (Country)

💬 Last Word

“If the industry wants a trusted, authentic creative ecosystem, the platforms must fix their algorithms. True excellence in concept, lyricism, and composition should be rewarded. No matter what tech stack you choose to build it.”

— Hybrid AI music entrepreneur RJ Deamer, via LinkedIn

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Copyright 2025-2026 Zinstrel, LLC - All rights reserved

Written by Marcus Lawrence, courtesy of composition platform Versey.ai
Special thanks to our paid subscribers: C.Y. Lee, Daryl Dekking, Lynn Clapp, Steve Clapp, Mete Dibi, Daniel Lares, Dexter Garcia, Matthew Marturano, Sammy Stoltz, Tim Burley, Drew Thurlow, Sheila Spence, Lenny Skolnik, Màuhan Zonoozy, Matti Kuha, and Jacci Cenci-McGrody.

While Editor Marcus Lawrence is on holiday, guest voices are stepping in to keep the AI music conversation going. This guest post series closes out courtesy of Mark Devlin, CEO of AI music discovery platform UPCHART, with a look at who AI music is actually for — backed by two months spent personally rating and ranking 1,500 songs on his own platform. What follows is a composite of his recent blogs originally published at Upchart.ai.

Marcus will return on July 24.

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When I was young, my school friends would disappear every lunchtime to the Music Room, a room only they could access because they could play a musical instrument. I was never allowed in. I was never invited in. I couldn’t play an instrument.

Fast forward to now. These days, everyone seems to agree there are two kinds of music: AI music and human music. The split is treated as obvious, self-evident, barely worth questioning. But is it?

When you say “human music” has more value than AI music, stop and think about who you’re actually including in that category. It’s not humanity, but rather a fraction of it. The people who could afford instruments and lessons. The people whose bodies let them play. The people who happened to live near a scene, or know the right producers, or get lucky enough to be heard. The people who made it through a system that was never designed to let most people through.

Everyone else? They’ve been listeners. That’s all that was on offer.

We’ve lived with that arrangement for so long we’ve started to mistake it for nature. It isn’t. It’s economics. It’s gatekeeping dressed up as quality control. And now that a technology has come along that tears those gates off the hinges, the gatekeepers are calling it an attack on humanity.

Why AI music is pro-human

Let me tell you who AI music is actually for.

It’s for the disabled person who has never been able to hold an instrument that needs two working hands. The ones who could never get their voice into a microphone and have it sound like them. Their songs, finally out in the world. AI music gives them a freedom they thought they could never have.

It’s for the millions of people who have always had music in them: melodies, lyrics, entire songs, but no path to get them out.

It’s for the musicians who’ve spent years crafting something real and original and never got within shouting distance of the resources needed to realise it properly. Not the famous ones; the ones you’ve never heard of. The ones who know exactly what their record should sound like and could never afford to find out if they were right.

I’ve spent two months rating and ranking hundreds of these songs, hundreds of these creators, and here’s what I’ve found:

1. A surprising share of the 3,000 songs submitted to UPCHART are strong — some good enough for radio as-is. I rarely rank anything less than 3 out of 5.

2. The sheer inventiveness of AI-generated songs is astounding: fantastic, original guitar and keyboard motifs and solos, unusual but interesting beats, soulful voices, atmospheres, and some of the best singing I’ve ever heard.

3. I haven’t heard much repetition or slop at all. Most songs are distinct creations. Songs with human-written lyrics tend to be the standouts — which may explain where some of the slop accusations come from in the first place.

4. Many people are reworking old demos and songs into stunning modern productions (myself included).

5. Some of the best songs rework elements of legacy bands and extend them. For example: What if Pink Floyd were still making great tracks, with modern production? What if a band continued in their spirit and sound? Familiar, but new.

6. We’re seeing people build song-based communities. One creator wrote songs about the Roman Empire and invited others to submit their own, sparking discussions about the music and the history.

7. The biggest insight, though, has been about what creators actually want. More than simply wanting their songs to be heard, and more than wanting their songs to rise up the charts, what AI song creators want most is to be valued as creators and acknowledged as people — especially when they face unwarranted anti-AI criticism.

Creators want to tell stories — not just the stories behind their songs, but their life stories as well. We’ve added spaces for creators to share and discuss the meaning behind their music, whether it’s personal heartbreak, adventures they have had, or a character they want to embody. And they tell us how they struggled to create before these tools came along and how they feel when they can finally make the music in their head. It’s a superpower to them.

Reading their stories has changed the way we think about creators.

The creativity was always there within these people. But now everyone has access to a new wave of creative tools. By expanding the group of people who can make music, it turns out that AI music may well be the most human music of all.

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🎧 Song of the Day: “GG EZ” by M.Sasuke

This explicit track was just the surprise No. 2 song on the SIQA top AI songs chart. It captures the high-energy, chaotic cycle of gaming frustration and obsession, where a confident player gets completely outplayed by a stronger opponent.

💬 Last Word

“Your talent gets you noticed. Your discipline gets you chosen.”

— A&R Executive Leslie Akrofi-Mantey, via LinkedIn

MORE ZINSTREL:
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Copyright 2026 Zinstrel, LLC - All rights reserved

Written by Marcus Lawrence, courtesy of composition platform Versey.ai
Special thanks to our paid subscribers: C.Y. Lee, Daryl Dekking, Lynn Clapp, Steve Clapp, Mete Dibi, Daniel Lares, Dexter Garcia, Matthew Marturano, Sammy Stoltz, Tim Burley, Drew Thurlow, Sheila Spence, Lenny Skolnik, Màuhan Zonoozy, Matti Kuha, Jacci Cenci-McGrody, and Jonathan Barrios.

While Editor Marcus Lawrence is traveling, guest voices are stepping in to keep the AI music conversation going. Today’s post comes from Rasha Rahman, founder and CEO of HumanStandard, the AI music detection platform he built to help protect provenance and listener trust. It’s the tool that has labeled Fenix Flexin’s “RUBBERZ” as AI-generated. Today he’s making the case directly to AI music creators for why detection, done right, is a net positive for AI creators rather than a threat to them.

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As an AI creator, you have probably experienced this recently: You spent time and effort working on a new piece. You feel good about it and decide you want to share it for others to enjoy. The comments start flooding in, but unfortunately, most of them are spamming the same thing:

“Is this AI?” “This is AI slop.”

Beneath the witch hunt, there may be genuine fans of your work. But they get buried, and the algorithm keeps sending the piece to people focused only on whether it was AI-generated.

And as long as there are people commenting on how it’s AI — and not on the actual work itself — you will continue to be shown to the wrong people. The algorithm will send your content to those who comment and interact with it. And these are the wrong people to interact with. They are not the people who give genuine feedback about your work, which is what every artist needs to grow and expand their creativity.

And this is why AI detection is important. I started HumanStandard because I believe ambiguity is the enemy.

Clarity Can Tone Down the Outrage

Let’s visualize this to understand better.

Imagine you are watching your favorite Olympic sport, the 100 meter dash. There are eight athletes competing. The person who takes first place is a beast, and they didn’t use any performance enhancement drugs. But second and fifth place used steroids.

At first, no one knew this. A month later, it’s leaked that second place did in fact use steroids. Immediately there’s mass outrage and a desire for them to return their medal. Tons of people will badmouth the second place athlete, without even batting an eye about the fifth place athlete who committed the same action.

But now imagine while they were competing, there was a little indicator on the second and fifth place shirts that said “performance enhanced athlete.” Human behavior will view the game differently. Yes, there will be people who think third place should have been second all along, but there won’t be the same backlash for them to “return” their win.

Also, the enhanced athlete who got fifth place will normalize that steroids are only as good as the person who is taking them.

You could take this a step further and create a whole new game that separates the two. And that’s exactly what happened.

This year brought the inaugural Enhanced Games, where athletes were allowed to use performance-enhancing drugs under medical supervision across multiple sports.

What is interesting about these games is that some people that broke records, and some people that did worse than natural Olympians. And in this space, there was freedom to actually judge why their enhancements worked or didn’t work.

We will be stuck on “Is this AI?” or “This is slop.” When everyone is aware of what is AI or not, then viewers will begin to split correctly, leaving those who are interested in the AI creation to be able to discern the difference and judge the work on its own terms.

And the ironic and unintuitive thing is that “AI Creator” is not a fair category for AI artists as it puts everyone in the same box, but labeling their songs as AI created is actually how we start to discern those differences.

Art Authentication is Nothing New

As AI detection becomes a norm in the music industry helping discern what is AI or not, I want to quickly give a brief history lesson on art authentication.

Art authentication has always existed. It wasn’t used as a way to police what medium artists used, but rather, to show honestly where the origin of something was from.

When photography first came out, it was treated harshly similarly to AI music. But when the labeling of said works as photographs began to normalize, no longer did it feel like deception, but actually understood as its own medium. Then discernment began on what was “good” or “bad” photography.

It wasn’t competing against art anymore, and someone making realism art was not put in the same category as someone posting photos. This allowed realism art to mature.

If we want to be true modernists and accepting of future forms of art, detecting and labeling AI content as AI is how we start to pursue that. As long as AI music is conflated/mixed with human music, it will never get to expand and evolve into its own thing.

Provenance is how we lead to attribution. And ambiguous attribution because of no detection hurts the pockets of most artists.

You wrote the lyrics to your song, but because you generated it in Suno, no one will care. But, for example, when HumanStandard checks your song and our hybrid model can tell that the track was generated as an instrumental in Suno, you can take pure credit for the voice and the lyrics which you, the human created.

Despite the belief that AI detection means anti-AI, at HumanStandard, we genuinely want to celebrate human-created works, even if they have AI in them. And we will do a much better job at describing that nuance versus the outside mob. This is why AI music detection (and all other AI content detection) is pro-everyone.

Both the human-only creator and the AI-creator want the same thing. They want their works to be recognized and judged on the work itself. We can live in a world where AI music thrives in its own lane — with its fans, and even eventually its own awards.

Nobody has to feel duped. And nobody has to hide.

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🎧 Song of the Day: “Blah Blah Rah” by Ladi Shalaya

This bombastic, self-assured, aggressive R&B pop track sticks it to the haters.

💬 Last Word

“Musicians aren’t rejecting technology because they don’t understand it. What they are doing is explicitly rejecting systems that make them feel as though their work, voice, catalog, taste, and culture can be absorbed into someone else’s product without their consent. That concern can’t be answered by pumping out features or funding rounds.”

— Ryan Merchant, Head of Global Comms & Artist Partnerships at Moises, via LinkedIn

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Written by Marcus Lawrence, courtesy of composition platform Versey.ai
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