Artificial intelligence didn’t knock on the door of the music industry — it walked straight in. What started as a promising creative tool has rapidly evolved into a systemic challenge for streaming platforms, artists, and rights holders. The question is no longer whether AI belongs in music, but how its unchecked expansion is reshaping the entire ecosystem.
Few numbers illustrate this better than the one recently disclosed by Deezer: over 60,000 AI-generated tracks uploaded every single day. According to the platform, a substantial share of these tracks exists for one purpose only — to exploit streaming systems through fraudulent listening behavior.
This is where the debate stops being theoretical.
From Creative Tool to Industrial Abuse
AI itself is not the enemy. In fact, it has already proven its value as a compositional assistant, a sound-design accelerator, and a production aid for legitimate artists. The problem begins when creation is replaced by multiplication.
Streaming platforms were built on metrics: volume, regularity, engagement. AI understands those rules perfectly — and exploits them ruthlessly. Thousands of tracks can now be generated in minutes, each subtly different, each optimized to sit unnoticed in background playlists.
At that point, music is no longer meant to be heard.
It is meant to occupy space.
And when space becomes the objective, creativity becomes collateral damage.
How Fake Artists Learned to Game the System
This industrialization of AI music has given birth to a new kind of profile: the fake artist. These accounts are rarely convincing, yet they are everywhere.
They share common traits. Anonymous names, no biography, no visuals, no social presence, no live performances — sometimes not even a coherent artistic identity. Entire networks of such profiles are often managed by the same entity, each releasing dozens of near-identical tracks under different aliases.
The intention is never to build an audience.
It is to harvest micro-royalties at scale.
In this model, listeners are irrelevant. Algorithms are the real audience.
When Platforms Start to Feel Like a Playground
As this content floods catalogs, the consequences ripple outward. Recommendation systems lose precision. Discovery playlists become diluted. Genuine artists are pushed further down the visibility ladder — not by better music, but by louder automation.
What emerges is a chaotic environment, increasingly compared by industry insiders to a digital schoolyard: noisy, unregulated, and polluted by actors who have nothing to lose and everything to exploit.
Listeners don’t always notice immediately. But they feel it. Trust erodes quietly — and when users stop trusting discovery, they stop engaging altogether.
That’s the real danger.
Copyright in the Age of Machines
If the economic impact is worrying, the legal one is even more fragile. Copyright law was never designed for machines trained on millions of existing works.
AI-generated music lives in a grey zone. Is it original? Is it derivative? Who owns it — the developer, the user, the model itself? And what happens when training data includes copyrighted material?
For now, regulation lags behind reality. This legal vacuum allows questionable practices to flourish, particularly when content is distributed under disposable identities that vanish before accountability can catch up.
For platforms, this is not just an ethical dilemma — it is a legal time bomb.
Not All AI Music Is the Problem
It’s important to draw a clear line: AI-assisted music is not the same as AI-generated spam. Many artists use AI transparently and creatively, as a tool rather than a shortcut. These practices enrich the ecosystem rather than pollute it.
The crisis lies elsewhere — in industrial misuse, mass automation, and deliberate system gaming.
Confusing innovation with exploitation would be a mistake. Ignoring exploitation would be worse.
Deezer Draws a Line in the Sand
Faced with this reality, Deezer has chosen action over denial. By deploying proprietary detection systems capable of identifying AI-generated content at scale, the platform has begun excluding fraudulent tracks from algorithmic recommendations and cutting off monetization tied to suspicious listening patterns.
The message is clear: AI is welcome — abuse is not.
Other platforms are watching closely. Some will follow. Others may hesitate, especially those benefiting from inflated catalog growth and engagement metrics. But the direction is set.
What’s Really at Stake
This is not just a technological arms race. It’s a question of trust, value, and survival.
If streaming platforms allow automation to overwhelm artistry, they risk hollowing out their own foundations. Music turns into background noise. Discovery becomes meaningless. Artists disengage. Listeners drift away.
The industry now faces a simple choice.
Either platforms clean up their playgrounds —
or they let the noise bury the voices that made streaming matter in the first place.
And this time, the noise isn’t coming from amplifiers.
It’s coming from algorithms.
