AI Music Startups Face Legal Battles as Major Labels Fight to Protect Copyrights

The music industry is facing a significant challenge from AI-generated music, which has the potential to disrupt the field similarly to how Napster once revolutionized—and threatened—music distribution. Unlike other creative industries, the music sector benefits from a robust legal framework and established copyright protections, giving it a strong position to combat AI-generated content. AI tools like those from Suno and Udio allow users to generate new songs with minimal effort, often by just typing in a few descriptive words. For instance, Suno's AI can produce an entire song when given a prompt such as "bossa nova song using a wide range of percussion and a horn section about a cat, active, energetic, uptempo, chaotic." However, these tools are more likely to be used by content creators seeking background music for videos or other media rather than by consumers looking to generate music for personal use. Despite this, the generated music is often of low quality and has been criticized for its lack of creativity and emotional depth. The primary concern lies in the impact on lesser-known artists and producers who create background music for various commercial uses, such as playlists, advertisements, and hold music. These artists are particularly vulnerable because AI-generated music can flood the market with low-cost alternatives, potentially undermining their livelihoods. David Hughes, a tech consultant and former CTO of the Recording Industry Association of America (RIAA), notes that the market for specific genres like meditation music has been saturated by AI, making it difficult for human artists to compete. The music industry has taken legal action to protect its interests. Major labels, including Universal, Sony, and Warner, have sued Suno and Udio, alleging that these companies illegally used copyrighted material to train their AI models. Both Suno and Udio have acknowledged in court documents that they used copyrighted songs in their training data, claiming it was fair use. Suno's defense argues that it included "essentially all music files of reasonable quality that are accessible on the open internet," adhering to paywalls and password protections. Udio has not explicitly stated how it acquired its training data. Several legal precedents could influence the outcome of these lawsuits. In Bridgeport Music v. Dimension Films, the US Court of Appeals ruled that even small samples of music must be licensed, setting a strict standard for copyright infringement in music. Similarly, Grand Upright Music v. Warner Bros. Records affirmed that sampling without permission is illegal, with the court famously opening the decision with "Thou shalt not steal." These rulings suggest that music may receive stronger protections against AI training compared to other creative works. James Grimmelmann, a professor at Cornell Law School, notes that if an AI model generates songs that closely resemble copyrighted works, it could be seen as infringing on those rights. In May, the Register of Copyrights Shira Perlmutter released a report stating that AI training on pirated collections of copyrighted works and distributing them could harm the market for those works, further aligning with the music industry's stance. Another recent legal case involving Anthropic highlighted that using legally acquired books for training data may be fair use, provided the outputs do not infringe on copyrights. In contrast, a ruling by Judge Vince Chhabria in a case against Meta indicated that market dilution—the creation of competing works—could be a valid claim of harm, potentially favoring the music industry. Suno and Udio may face additional legal hurdles due to the availability of licensing markets for music training data. While it is challenging to license books for AI training due to fragmented rights, the music industry has a more structured licensing system. Music licenses for AI training cost between $1 and $4 per track, and high-quality datasets can range from $1 to $20 per minute. This well-established market makes it harder for companies to argue that licensing is impractical. Kuok Meng Ru, CEO of BandLab, advocates for a licensing approach. BandLab's AI tool, SongStarter, helps musicians by generating initial tracks, but the company ensures that artists are compensated through its licensing program. Artists can opt into AI licensing, and BandLab negotiates deals on their behalf, ensuring they receive fair compensation. Ed Newton-Rex, a former vice president at Stability AI, emphasizes the ethical and legal importance of licensing music for AI training. He left his position at Stability AI after the company determined that using copyrighted data for training was fair use, a stance he strongly disagrees with. Newton-Rex has shown that Suno's AI can produce songs eerily similar to copyrighted works, highlighting the potential for market disruption and copyright violations. Industry insiders and legal experts agree that the music industry is better positioned to fight AI-generated content than other creative fields. The combination of strong copyright laws, organized licensing structures, and historical legal victories provides a solid foundation for legal challenges. However, the ultimate resolution of these lawsuits will depend on how courts interpret fair use and the extent to which AI-generated music can be deemed a derivative work. Regardless, the music industry's proactive stance may set a precedent for how other creative industries will handle similar issues in the future.