Google Sued by Indie Musicians Over AI Music Amid Escalating Battle Against Tech Giant

A group of independent musicians has filed a sweeping lawsuit against Google, alleging the tech giant used copyrighted music from YouTube to train its artificial intelligence music generator without permission — an accusation that could reshape how AI companies develop creative tools.

The case, Kogon et al v. Google LLC, was filed in federal court and targets Google’s AI music technology, including Lyria 3 and ProducerAI. According to the complaint, the company used its control over the music distribution ecosystem — from YouTube uploads to copyright identification systems — to build a competing product using artists’ own work.

“This is a case about what Google took, what it built with it, and what it never paid for,” the lawsuit states.

The plaintiffs include a coalition of independent musicians from across the country, including singer-songwriter Sam Kogon, composer Magnus Fiennes, producer Michael Mell, the R&B group Attack the Sound and Chicago-based band Directrix.

Their complaint argues that Google leveraged its ownership of YouTube and its ContentID copyright system to train its AI music models on vast amounts of artist-created content.

“Google owns the platform where independent musicians distribute their music. Google runs the system that identifies who owns it. And then Google used both to train a product that competes with the very artists who trusted it with their work,” said attorney Ross Kimbarovsky of Loevy + Loevy, which represents the musicians.

The lawsuit claims Google copied millions of songs, stripped them of identifying copyright information and incorporated them into its AI training systems.

“That is not innovation. It is theft at scale,” Kimbarovsky said.

The case marks the first major lawsuit targeting Google’s entry into the rapidly expanding AI music market. It follows similar copyright battles against AI music generators such as Suno and Udio, which have already faced lawsuits from major record labels and independent artists.

According to the complaint, Google used its existing infrastructure to pivot from distributor to competitor.

“Google had every opportunity to develop this product legally,” the lawsuit states. “Google chose not to do so, not because licensing was impossible, but because copying was faster and cheaper.”

In addition to copyright infringement claims, the lawsuit alleges violations of the Digital Millennium Copyright Act and the Illinois Biometric Information Privacy Act, arguing that Google may extract voiceprints from vocal recordings without permission.

Experts say the case highlights unresolved legal issues surrounding generative AI and creative ownership.

“The core issue here isn’t just about technology — it’s about consent and provenance,” said Ravi Sawhney, CEO and founder of RKS Design.

“Generative AI systems are incredibly powerful, but they rely on massive datasets that often include creative works produced by musicians, writers, and artists. When those works are used without clear licensing or permission, it creates tension between technological progress and the rights of creators who built the cultural foundation these systems learn from,” Sawhney declared.

Courts may ultimately focus on whether training AI on copyrighted material qualifies as fair use, whether companies should obtain licenses for training data, and how transparent developers must be about their datasets.

“Data provenance — knowing exactly where training material came from — is going to become a central issue,” Sawhney mentioned. “As AI platforms mature, the expectation will be that developers can demonstrate how their models were trained and whether creators were properly represented in that process”

While the lawsuit seeks damages and class-action certification, industry observers say the broader outcome could reshape how AI and the music industry coexist.

“We’re probably moving toward new frameworks rather than a single court decision that settles everything,” Sawhney explained. Those frameworks could include licensing systems for AI training data or new collective rights models that allow creators to share in the value generated by AI tools. In the meantime, “creators across every field need to stay vigilant about protecting their rights.”

Ultimately, he said, the success of AI in creative industries depends on maintaining trust with the artists whose work fuels these technologies, noting, “When creators feel their work is respected and there’s a clear framework for consent and compensation, the ecosystem becomes stronger for everyone — artists, technology companies, and audiences.”