Suno adds watermarking and download limits amid copyright pressure
Suno will watermark songs and cap downloads as copyright fights intensify, testing whether AI music can be traced instead of mass-spammed.
Suno said it will roll out durable audio watermarking and fingerprinting in the coming weeks and tighten download limits to curb spammy AI tracks and platform abuse. In a responsible AI post, co-founder and chief executive Mikey Shulman set out four principles, including: “AI should enable originality, not imitation.”
The move lands under sharper legal pressure. Suno’s new policy push came about a week after a German court held the company liable for infringing German song copyrights in a case involving GEMA, the country’s music rights collection society. Suno also said it will use audio watermarking and fingerprinting to make Suno-made music easier to detect and to prevent misuse on other streaming platforms, a sign that the company is trying to make its output more traceable as it faces growing scrutiny over how AI music circulates online.
The scale of Suno’s service explains why the changes matter. A March 11 interview said the company was generating 7 million songs a day, while a LinkedIn post quoting Peter Yang said Shulman said Suno had grown to 25 million users creating music. Based in Cambridge, Massachusetts, Suno has also amassed a broad consumer footprint, with the Google Play listing showing 2.1 million reviews and the App Store describing it as an AI music generator that turns ideas into full songs instantly.
That reach has made Suno a flashpoint in the fight over AI labeling. Musicians and critics have pushed streaming platforms to mark AI-made tracks more clearly, and Suno’s new rules aim to answer that pressure with technical detection instead of relying only on voluntary disclosure. The company also adopted Musixmatch’s copyright-detection service and paired that with its new download limits, which are meant to stop users from mass-downloading large numbers of songs in ways that can fuel spam or platform abuse.
The unanswered test is whether watermarking and fingerprinting can do more than defend Suno’s reputation. If the markers are truly durable and tamper-resistant, they could help platforms identify AI-generated tracks after reuploads and reposts, not just inside Suno’s own app. If they are easy to strip or ignore, the policy will do less to separate legitimate experimentation from industrial-scale noise than to show regulators and the music business that Suno is trying to police itself.
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