UMG and Sony can pursue Suno over alleged YouTube ‘Stream Ripping’ to train AI
A US judge has allowed UMG and Sony to pursue Suno over alleged YouTube ‘stream ripping’ to train its AI models. Here’s what artists need to know.
A US judge has allowed Universal Music Group and Sony Music to add a new claim against AI music company Suno, alleging it bypassed YouTube’s technology to download copyrighted recordings for AI training. Here’s what the case could mean for musicians, producers and the future of AI-generated music.
The legal battle between the music industry and AI music generators has taken another significant turn.
A US federal judge has given Universal Music Group (UMG) and Sony Music Entertainment permission to pursue a claim accusing Suno of using so-called “stream ripping” to obtain copyrighted recordings from YouTube and use them to train its AI music models.
The decision doesn’t mean Suno has been found guilty of piracy. Instead, Judge F. Dennis Saylor IV has ruled that the labels have presented a plausible enough case for the claim to move forward while the court examines the evidence.
For musicians and producers, however, the development is significant. The case highlights one of the biggest questions surrounding generative AI in music: where does the training data come from, and should artists be paid or asked for permission when their recordings are used?
What is ‘stream ripping’?
The term might sound technical, but the basic idea is fairly straightforward.
The labels allege that Suno obtained music from YouTube by using software designed to download audio from online videos. Their amended complaint names open-source tools including YT-DL and YT-DLP, alleging that Suno used them to bypass YouTube’s technical protections and extract copyrighted recordings.
At the centre of the new claim is YouTube’s “rolling cipher”, a technical measure that the labels say is designed to prevent unauthorised access to underlying media files.
The labels argue that bypassing this technology amounts to circumvention under Section 1201(a)(1) of the US Digital Millennium Copyright Act (DMCA).
Suno has previously disputed the legal basis of this argument, including questioning whether the technology in question actually controls access to the copyrighted works in the way required by the DMCA.
Judge Saylor said determining exactly how the technology and downloading tools work will require more evidence. For now, though, he found that the labels’ allegations were sufficient to proceed.
This is separate from the bigger copyright question
It’s worth making a distinction here.
UMG and Sony are already suing Suno over the alleged use of copyrighted sound recordings to train its AI system. The stream-ripping claim is an additional legal argument focused specifically on how the recordings were allegedly obtained.
The court has not yet decided whether Suno’s use of copyrighted recordings to train its AI model constitutes fair use.
That question remains one of the central issues in the case, with fact discovery scheduled to close on September 30, 2026, according to the latest reporting. The parties are then expected to seek summary judgment on the wider question of whether training an AI model on copyrighted recordings without a licence can qualify as fair use.
In other words, there’s still a lot to be decided.
Why this matters to independent artists
For independent musicians, this isn’t simply another major-label legal dispute.
The argument over AI training affects anyone whose music is publicly available online.
Independent artists often upload their music to YouTube, Spotify, SoundCloud and other platforms specifically because they want people to hear it. But being publicly available doesn’t necessarily mean an artist has agreed for their recordings to be downloaded, copied and incorporated into an AI training dataset.
That’s one of the biggest tensions in the current AI debate.
Listening to a song and using a song to build a commercial AI model are two very different things.
The music industry is increasingly asking where that line should be drawn.
Independent artists are already taking Suno to court
The major labels aren’t the only rights holders pursuing Suno.
Country artist Tony Justice, alongside his label and publishing company, has brought a proposed class action against Suno representing independent artists, songwriters and producers.
In August, Judge Saylor refused to dismiss most of that case, allowing claims involving alleged AI output infringement and the alleged circumvention of YouTube’s technology to proceed.
The case is particularly relevant to independent musicians because the plaintiffs argue that creators outside the major-label system also need meaningful protection as AI companies build increasingly powerful music-generation tools.
That could make the coming months particularly important for independent artists.
The music industry is moving towards licensing
Interestingly, while Suno continues to face litigation, the company is also beginning to move towards licensed music.
In August, Suno announced a deal with BMG covering recorded music and publishing repertoire, with the agreement described as opt-in for artists and songwriters and intended to settle Suno’s previous use of BMG’s catalogue.
Suno has also said that it plans to introduce a new generation of models “developed in partnership with the music industry”, while retiring its previous models.
That shift could prove important.
Rather than the industry having to decide whether AI music should exist at all, the bigger question may increasingly become what a fair AI music ecosystem looks like.
That could include licensing agreements, artist opt-in systems, compensation models and clearer rules around training data.
AI isn’t going away, but the rules are changing
The Suno case comes at a time when governments, streaming services, record companies and artists are all trying to establish where AI fits into the music industry.
Recent developments have included streaming platforms introducing greater transparency around AI-generated music, while Australia’s ARIA Charts has moved to exclude fully AI-generated recordings from chart eligibility.
Meanwhile, a German court recently ruled that Suno infringed copyright by processing songs without the necessary rights in a case brought by German collecting society GEMA. Suno has said it is considering its options, including an appeal.
The direction of travel is becoming increasingly clear: AI companies are going to face more questions about where their training material comes from.
What should artists be doing?
For independent artists, there’s no need to panic or stop using AI tools altogether.
Instead, be more careful about understanding the tools you’re using.
Before incorporating AI-generated material into a commercial release, check the platform’s terms around ownership, commercial use, training data and licensing. Keep track of how your music is created, particularly if you’re using AI alongside your own recordings or production.
It’s also worth keeping your original project files, stems and recordings. As AI identification and rights-management systems become more sophisticated, having a clear record of your creative process could become increasingly useful.
And, as always, make sure your music is properly registered and distributed with accurate metadata.
The bigger picture for musicians
Perhaps the most important takeaway from the Suno case is that the AI music debate is moving beyond “Can AI make music?”
It clearly can.
The harder questions are now about ownership, consent, compensation and transparency.
If an AI company can legally license music from artists and rights holders to train its models, there is a potential path towards an ecosystem where technology and human creativity can coexist.
But if copyrighted music can simply be scraped from the internet and used without permission, independent artists could find themselves competing with systems trained on the very music they spent years creating.
That’s why this case matters even if you’ve never used Suno.
The decisions being made now could influence how music is created, distributed and monetised for years to come.
For independent artists, the best response is to stay informed, understand where AI fits into your own workflow and keep building your catalogue and audience. The technology is changing quickly, and the rules around it are changing just as fast.