Over 30% of all new music on Deezer is AI-generated – and most people can't tell the difference

97% of listeners can't tell AI from a human

17 Dec 2025, 12:07 · TechRadar

News By John-Anthony Disotto published 17 December 2025

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34% of new music on Deezer is AI-generated
97% of listeners can't tell the difference between AI music and human-made tracks
Where does it end and what needs to be implemented to stop the slop?

If you’ve listened to new music recently and thought it sounds a bit soulless, there’s a decent chance you weren’t imagining it.

According to new data from streaming service Deezer, 34% of all new music uploaded to the platform is now fully AI-generated. That’s over 50,000 AI-made tracks being uploaded every single day.

If you thought that was bad, what’s more unsettling is that almost nobody can spot it - Deezer also commissioned a study that shows 97% of people "can't tell the difference" between AI and human-made music.

A flood of AI music

Deezer's research was conducted by blind tests across eight countries, where people overwhelmingly failed to identify which tracks were AI-generated, even when actively trying to do so.

That flood of synthetic songs is being driven by how easy AI music tools have become to use. You no longer need a band, a studio, or even much musical knowledge. With an AI app like Suno, a prompt, and a few clicks, you can now produce tracks that are good enough to pass as human work, at least to most ears.

While AI music is everywhere in terms of uploads, it still barely registers when it comes to actual listening. Deezer says fully AI-generated tracks account for around 0.5% of total streams, suggesting listeners still gravitate towards music made by real artists, even if they can’t always tell why.

Where does this stop?

That gap between volume and popularity hasn’t stopped concern from spreading across the industry. In the same study, around 80% of people said AI-generated music should be clearly labelled on streaming platforms. Many also worried about the impact on artists’ livelihoods, particularly when it comes to AI models being trained on copyrighted music without consent.

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