UMG and Sony Fight to Keep Suno's AI Training Data Scale Public in Copyright Case
Universal Music Group and Sony Music Entertainment filed a legal memorandum urging a federal court to reject Suno's bid to keep secret the total number of audio files used to train its AI music model—the figure the labels call the 'Model Training Figure.' The labels argue there is a 'strong presumption of public access' to court pleadings, that the number speaks directly to the nature and extent of Suno's copying, and that Suno's competitive harm claims are 'speculative.' The filing accompanies a separate motion seeking to add 61,026 additional recordings—identified via Audible Magic audio-fingerprinting of Suno's training data—to the nearly two-year-old copyright lawsuit. Suno has opposed that expansion, arguing the labels 'unduly delayed' and that broadening the case would deny it a timely ruling on its fair use defense.
THE BREAKDOWN
This case is becoming the defining legal test for whether AI music generators built on unlicensed recordings can survive under copyright law—and the outcome will directly shape which AI music tools brand managers and music supervisors can legally use in campaigns. The fight over sealing the training data figure is tactically significant: if the number is as large as the labels appear to believe, it would undercut Suno's fair use argument and potentially establish that mass-scale copying cannot qualify as transformative use under copyright law. Music rights managers advising artist clients should track the Audible Magic fingerprinting methodology being used here—it's likely to become a standard for future AI training data audits across the industry. Agents with musician clients who haven't registered and delivered their full catalogs through rights management services are exposing those artists to scenarios where their works have been used with no recourse. Watch for the court's ruling on the sealing motion; it sets disclosure precedent that will affect every pending AI training data case.
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