Streaming services are facing a new kind of mess — not just piracy or low payouts, but millions of low-quality, AI-generated tracks that flood catalogues, waste listeners’ time and, in some cases, attempt to siphon tiny royalty payments. Over the past year the problem has accelerated because generative AI tools make it trivially easy for anyone to mass-produce short, repetitive or voice-cloned tracks and upload them to stores and services. Now platforms, industry groups and lawmakers are moving to contain the damage. The moment matters: it’s about protecting artists’ voices, rebuilding trust in discovery systems and making sure streaming revenue reaches real creators.

Spotify’s recent announcement forced the issue into the open. The company says it has removed more than 75 million “spammy” tracks from its catalogue in the past 12 months and published a package of policy and product changes to target impersonations, mass uploads and undisclosed synthetic music. That figure is eye-watering — roughly close to Spotify’s entire active catalogue — and explains why the company is racing to add detection tools, metadata standards and new enforcement rules.

What Spotify is changing (and why it matters)

Spotify’s approach is multi-pronged. The company is rolling out a dedicated music spam filter to tag and restrict uploads that look like bot-generated or manipulative content; it is tightening its rules on unauthorised vocal impersonation (deepfakes); and it says it will support an industry metadata standard — developed through DDEX — that allows distributors and labels to disclose whether AI was used in vocals, instrumentation or post-production. Spotify frames these moves as a way to protect listeners and rightful artists while permitting legitimate creative uses of AI, but the new tools also give the platform the ability to demote and ultimately remove bad actors.

A technical quirk of streaming economics helps explain the rush to act. Historically, many platforms paid tiny fractions of a cent per stream but counted a play after a short threshold (Spotify has previously paid out on plays longer than 30 seconds). That meant automated uploads and intentionally short tracks could collectively generate royalty streams with very little effort. Platforms say most of the spam didn’t meaningfully affect user engagement, but it clogged artist feeds and risked distorting recommendations and royalty splits — precisely the problem Spotify wants to limit with its spam filter and updated payout safeguards.

Spotify’s move did not happen in a vacuum. Major labels and rights organisations have been warning about AI-enabled abuse for months; several have publicly endorsed stronger platform safeguards. At the same time, governments and industry bodies are discussing legal responses. In the U.S., activists and music industry groups support measures such as the NO FAKES Act, which would create stronger protections against unauthorised voice and likeness deepfakes; major organisations, including players from the Recording Academy, have backed this kind of legislative effort. Meanwhile YouTube and other platforms have also updated policies to allow takedowns of unauthorised vocal clones and to require disclosure for synthetic content in some formats.

The DDEX metadata framework is being updated so labels, distributors and aggregators can tag tracks with machine-readable information about whether AI played a role (for example, “AI-assisted instrumentation” or “AI-generated vocal”). That kind of transparency helps curators, playlist editors and listeners make informed choices and creates an audit trail should impersonation claims arise. But disclosures rely on truthful reporting; detection systems and audits will still be necessary to catch bad actors who try to game the metadata. The standard is an important step, but it’s not a silver bullet.

What this means for artists and rights holders

For artists, the clean-up is broadly positive: it reduces the risk of impersonation, protects the integrity of streaming reports and helps ensure that royalties aren’t siphoned off to low-effort uploads. Practically speaking, creators should register works correctly, ensure distributors provide accurate metadata, and be ready to file impersonation claims if they find unauthorised clones. Labels and rights organisations should also push for faster takedown processes and improved verification for high-volume uploaders. The industry response is a reminder that technology alone won’t fix the problem — platforms, labels, creators and lawmakers must cooperate.

Risks and unintended consequences to watch for

Any automated filter risks false positives. If platforms push too hard without nuanced detection, legitimate grassroots uploads — experimental AI art, short interludes or authentic DIY work — could be caught in the net. Transparency from the platforms about how filters operate, a clear appeals process, and human review for edge cases will be essential. There’s also a reputational risk: artists who already distrust streaming platforms over royalties will scrutinise whether this clean-up is substantive or merely PR.

What comes next — practical takeaways for readers

Expect a period of fast iteration. Platforms will deploy more sophisticated AI-detection tools; metadata disclosure via DDEX will become more common; lawmakers may accelerate bills that define legal protections against misuse of voice and likeness; and rights-holders will test new verification workflows for distributors. For readers and fans, this should mean fewer deepfake uploads in your feed and cleaner recommendations; for artists it should mean better tools to protect a voice that, quite literally, belongs to them.

Join the conversation: Do you think streaming platforms should ban all AI-generated music unless it’s clearly labelled, or should AI work be allowed freely with transparency? Vote in the comments and tell us why.