A coalition that includes all three major record companies alongside HYBE, Believe, BMG, Concord, Dirty Hit, Glassnote Records, Mom+Pop Music and Partisan Records has proposed a new set of principles governing when music created with generative artificial intelligence should be allowed to compete on official music charts.
AI itself isn’t being banned. Under the proposal, musicians could continue using generative AI as part of their creative process. But recordings would need to remain “substantially human made,” use authorized and lawful AI services, respect copyright and personality rights, disclose appropriate AI involvement and remain free of streaming or chart manipulation.
In other words, the industry isn’t necessarily coming for the musician who used AI to help create a backing track. It is coming for the computer that generated 8,000 songs before lunch and then sent an army of bots to stream them.
And judging by what is happening on streaming platforms, this conversation probably couldn’t wait much longer.
More Than Half of New Uploads Can Now Be AI
The scale is staggering.
Think about that.
On peak days, more new fully AI-generated tracks can arrive at Deezer than human-made ones. That doesn’t mean listeners are suddenly abandoning Beyoncé for Brian the Algorithm. Fully AI-generated music still represents only a small percentage of actual listening. The bigger problem is what accompanies some of it.
Deezer has reported extraordinarily high levels of fraudulent streaming associated with fully AI-generated tracks. That creates an economic problem extending far beyond philosophical arguments over whether a machine can make “art.”
Streaming royalties ultimately come from a finite pool of money.
If somebody can generate thousands of inexpensive tracks and manufacture millions of fraudulent streams around them, that activity can divert money and visibility away from legitimate musicians.
The industry’s argument therefore isn’t simply “robots aren’t artists.” It is also: robots shouldn’t be allowed to cheat.
The Industry Is Drawing a Line Between AI-Generated and AI-Assisted
In July, a separate coalition including the RIAA, IFPI, Recording Academy, SAG-AFTRA and other industry organizations proposed two voluntary labels for recordings: AI-Generated and AI-Assisted.
An AI-generated recording would include music in which generative AI created the entirety or primary creative elements, including a lead vocal, major instrumental performance or an essentially prompt-generated recording.
AI-assisted music is different. A human remains substantially responsible for the recording, including its primary performance, while generative AI contributes certain elements.
That is an acknowledgement that AI isn’t going away. Musicians are going to use it. The question is how.
AI Can Also Give Someone a Band Who Doesn’t Have One
Imagine an aspiring songwriter living in a small town. She can write melodies. She can write lyrics. She can sing. What she doesn’t have is a drummer or a bassist or a producer or a recording studio or $20,000.
Twenty years ago, those limitations could have prevented her from ever producing a professional-sounding recording. Technology has gradually demolished many of those barriers. Affordable digital recording did it. GarageBand did it. Sample libraries did it. Auto-Tune did it. Bedroom production did it.
Generative AI may demolish another one.
Academic research into generative music systems specifically identifies lowering barriers to music creation as one of AI’s potential benefits. Systems such as Suno, Udio, AIVA and Stable Audio allow people without access to traditional production resources—or even extensive formal musical training—to generate musical components that previously required musicians, studios and considerable money.
That can reasonably be called democratization. It can also reasonably be questioned.
Researchers examining the “democratization” argument around generative music have cautioned that giving everyone access to generation tools isn’t automatically the same thing as genuinely democratizing musical culture. It may simply transfer creative dependence from record labels, studios and expensive equipment to technology companies controlling algorithms and platforms.
Still, for the songwriter who cannot afford a band, the practical difference can be enormous. And that’s where “substantially human made” becomes a surprisingly difficult phrase.
How Much Human Is Human Enough?
Suppose our songwriter writes every lyric, melody, and the lead vocal.
But AI creates the drums, bass and orchestration according to her instructions. Is that substantially human? Probably.
Now suppose she writes the lyrics and asks AI to compose everything else. Still human enough?
What if she writes only the prompt? What if she generates 50 versions, chooses one, rearranges it, rewrites the chorus and records her own vocals? What percentage of humanity have we reached?
Nobody has produced a universally accepted mathematical answer. That ambiguity will be a point of contention. The coalition’s proposed chart principles depend partly on recordings being “substantially human made.”
The principle is easy to understand but the application will be much harder to police.
Listeners May Be More Complicated Than Either Side Thinks
Then we arrive at the people who ultimately determine whether any of this matters:
Listeners.
And the research is fascinating because audiences appear capable of holding contradictory ideas about AI music simultaneously.
A 2025 Deezer/Ipsos study involving 9,000 people across eight countries gave participants a blind listening test involving human and fully AI-generated music. Ninety-seven percent failed to correctly distinguish them.
That does not mean 97% preferred AI music. It means AI has become good enough that origin can no longer reliably be determined simply by listening. When people learned that, many weren’t delighted. More than half said they were uncomfortable about being unable to distinguish AI from human-made music.
That distinction matters enormously.
People may be perfectly capable of enjoying an AI-generated song while simultaneously believing that it should be labeled differently from human-created music.
Younger Listeners Aren’t Necessarily Saying “Who Cares?”
There is a tempting assumption that younger generations raised on algorithms, TikTok, virtual influencers and digital culture simply don’t care whether their entertainment is human.
The evidence is more complicated.
Luminate’s 2025 U.S. consumer research found that roughly a quarter to a third of listeners were comfortable with various applications of generative AI in music. Teenagers aged 13 to 17 were relatively comfortable with AI-generated lyrics, with 37% expressing comfort.
But subsequent Luminate research found something unexpected.
Rather than steadily becoming more accepting, Gen Z and Gen Alpha showed some of the largest increases in discomfort with generative AI in music between survey periods. Younger audiences may understand the technology better precisely because they encounter it more frequently. Familiarity doesn’t automatically equal acceptance. And perhaps the more useful question isn’t whether listeners will consume AI music. They already can.
The question is whether they will assign the same meaning to it.
Maybe We Need to Separate “I Like This Song” From “This Is Art”
Consider another possibility. A listener hears an AI-generated song and they save. They later use it for exercising. They don’t particularly care that nobody sat in a studio recording the vocals.
That doesn’t necessarily mean the listener considers the AI creation equivalent to Joni Mitchell writing “Both Sides, Now,” Prince constructing a record largely by himself or a K-pop group spending years developing the skills required to perform live. Consumption and cultural value aren’t necessarily the same thing.
We already make distinctions like this constantly. People listen to ambient rain recordings while studying without asking who the rain’s producer is. They use royalty-free background music in videos without developing emotional relationships with the composer. They listen to functional playlists designed for sleep, concentration or exercise.
AI music may flourish enormously in those environments. But fans don’t simply consume songs. They consume stories.
They follow artists through failures and breakthroughs. They watch concerts. They learn personalities. They debate albums. They buy merchandise. They travel to shows. They care who wrote the song and why.
AI can generate a voice. Generating a meaningful human biography is something else entirely. That may become one of the most important dividing lines in the future music business.
Research Already Suggests “Human” Carries Emotional Meaning
Experimental research into perceptions of AI-generated and human-composed music has produced another interesting contradiction.
In one 2025 study examining music and emotional response, participants sometimes expressed preference for AI-generated music. Yet human-composed music was more likely to be considered effective at eliciting the intended emotional state, while qualitative responses associated human music with qualities including imperfection, individuality and “soul.”
That suggests the eventual marketplace may not divide neatly into:
Human music = good. AI music = bad.
It could instead divide according to what listeners want from music.
For some purposes, listeners may care primarily about sound. For others, authorship itself may become part of the product. And that creates another possibility the traditional music industry should probably consider.
What Happens If AI Music Builds Its Own Music Industry?
Suppose official charts eventually adopt strict rules and fully generated AI music becomes largely excluded. Suppose major streaming services reduce its algorithmic visibility. Suppose certain platforms stop paying royalties on fully AI-generated recordings.
Does AI music disappear? Probably not. It may simply go somewhere else. We’ve seen this pattern repeatedly in the media.
When established systems don’t accommodate a new form of creation or audience behavior, alternative ecosystems emerge around it.
YouTube created an entertainment economy outside television. SoundCloud created its own musical movements. TikTok turned fragments of songs into a discovery engine powerful enough to influence the traditional charts. Independent creators built enormous audiences without traditional record labels. There is therefore a plausible future in which AI-heavy music develops its own platforms, communities, charts and stars.
Call it the Synthetic 100. I’m joking. Mostly.
We Could End Up With Two Music Cultures
By 2030, we could end up between different ecosystems. One emphasizes verified human performers, traditional songwriting credits, touring artists and recordings meeting strict human-authorship requirements. Another embraces generative music: virtual performers, endlessly customizable songs, AI-assisted independent musicians, interactive albums and music that changes according to the listener.
Neither necessarily eliminates the other. They may simply satisfy different desires. One gives you a musician to believe in. The other gives you exactly the music you want. And somewhere between them will probably sit the overwhelming majority of working artists, using AI selectively while remaining fundamentally human creators. That middle ground may ultimately matter more than either extreme.
The Real Fight Isn’t Humans Versus AI
The industry’s new proposal is easy to characterize as record companies trying to protect themselves from artificial intelligence. There is undoubtedly economic self-interest involved. Major labels have enormous catalogs, copyrights, artists and businesses to protect. But reducing the issue entirely to corporate protectionism ignores legitimate problems.
Artists should have control over whether their voices are cloned. Copyrighted recordings shouldn’t simply become free raw material because an algorithm can ingest them. Fraudulent streams shouldn’t determine chart positions.
And a person who uploads 50,000 automatically generated recordings shouldn’t necessarily receive the same treatment as 50,000 musicians individually creating songs. At the same time, the industry needs to be careful that protecting human artistry doesn’t accidentally mean protecting only musicians wealthy enough to create music through traditional means.
The teenager producing songs on a laptop deserves consideration too. So does the songwriter who cannot afford session musicians. So does the independent artist using AI to create an orchestra she could never hire. So does the listener who genuinely enjoys an AI-generated song.
The future probably isn’t a world where AI replaces musicians. Nor is it likely to be one where the industry successfully keeps AI outside the gates. It will probably be much messier.
Human artists will use AI. AI artists will attract human fans. Some listeners will demand labels. Others won’t care. New platforms may emerge. New genres probably will. Courts will argue about ownership, charts will argue about eligibility and musicians will continue arguing about what qualifies as music—something musicians were doing long before anybody invented artificial intelligence.
For now, though, Sony, Universal, Warner, HYBE and their allies are drawing their line.
AI can come into the studio.
It can help make the record.
It might even help write parts of it.
But if it wants to compete against human musicians on the charts, the industry’s message increasingly appears to be:
Please bring a human… preferably one with a navel.
