PolicyCulture

Munich court rules against Suno in GEMA case, a first big European AI music verdict

Illustration for the Suno GEMA ruling story

AI music copyright just met its first big European verdict, and Suno lost.

On July 31, 2026, the Regional Court of Munich I (case 42 O 763/25) ruled against Suno, the US AI music generator, in a case brought by GEMA, Germany’s music rights society. Six works were in dispute, including Alphaville’s “Forever Young,” Boney M.’s “Rasputin” and “Daddy Cool,” Helene Fischer’s “Atemlos durch die Nacht,” Alphaville’s “Big in Japan,” and the refrain of Lou Bega’s “Mambo No. 5.”

What the court actually found

The important detail is the reasoning, not just the result. The court did not simply find that Suno trained on the songs. It held that the recordings are reproducibly contained in Suno’s models, and that the outputs are recognizably similar to the originals, with Suno and not the user carrying the liability.

That distinction is why the court set this case apart from the US rulings that went the other way. It is not a verdict about what went into training. It is a verdict about what is still inside the model and what comes out of it.

What happens next

Suno must now disclose the revenues connected to the infringement so damages can be calculated. The amount is still pending, and the ruling can be appealed.

“This is a verdict of global significance,” GEMA’s CEO Tobias Holzmueller told Reuters.

Why it matters

Europe now has a court decision saying an AI music model can itself be the infringing artifact, with the provider on the hook rather than the user who typed the prompt. If that logic holds up on appeal, the training-data free ride may be ending in Europe, and every generative music company operating there will have to price that in.

A fair result for artists, or a wall in front of AI progress? This is the case that will be cited when that argument happens.

Sources

ANOTHER News is published by ANOTHER, an AI-native content agency. Daily coverage also runs on Instagram.