As artificial intelligence becomes increasingly capable of generating music, one of the most pressing questions facing the industry is deceptively simple: who owns AI-generated music? Behind this question lies a complex web of copyright law, authorship, ethics, and economic power. Unlike traditional music, where ownership is tied to a human creator, AI music challenges the foundations of how creative ownership has been defined for decades.
The Core Problem: Can AI Be an Author?
In the United States, copyright law is clear on one point: copyright protects human creativity. Works that are generated entirely by AI, without meaningful human involvement, are not eligible for copyright protection. The rationale is that AI lacks legal personhood and cannot be considered an “author.”
This creates a legal gap. AI-generated music is often commercially usable, widely distributed, and monetized, yet it may not be owned by anyone in the traditional sense. If a piece of music has no copyright, it can theoretically be copied, reused, or exploited by anyone. If it is restricted by platform terms of service, however, it cannot be used.
Human–AI Collaboration and Ownership
Ownership becomes more nuanced when humans collaborate with AI. Legal scholars argue that if a human plays a clear authorial role, the human-created elements of the work may be copyrighted. According to Daniel Gervais, a professor at Vanderbilt Law School, if the contributions of the human and the machine can be separated, copyright applies only to the human portion.
If the contributions are deeply intertwined, copyright may still exist—as long as the human exercised creative control over the final expression. This means that prompting alone may not be enough; there must be evidence of meaningful human decision-making, such as editing, arranging, or creatively shaping the output.
A relevant precedent comes from a book that used AI-generated images. While the book as a whole was copyrighted, the individual images were not. The U.S. Copyright Office ruled that the edits made to the AI images were “too minor and imperceptible” to qualify as human creativity. This highlights how high the bar is for AI-assisted works to gain copyright protection.
Training Data and the Question of Fair Use
Another major ownership controversy lies in how AI models are trained. Music-generating AI systems are trained on vast datasets of existing human-made music, often scraped from the internet without explicit permission. This has triggered lawsuits across creative industries.
Several high-profile cases illustrate the stakes:
- Universal Music Group sued Anthropic for training AI on copyrighted song lyrics.
- Getty Images sued Stability AI for using copyrighted images without authorization.
- The New York Times sued OpenAI for allegedly using its articles to train language models.
- Bev Standing, a voice actor, sued TikTok for using her voice without consent in text-to-speech tools.
The concern shared by artists is stark: “Artists are literally being replaced by models trained on their own work.” If AI systems profit from music they were trained on without compensation, ownership becomes ethically, and possibly legally, questionable.
Substantial Similarity and Legal Risk
For AI-generated music to infringe copyright, it must be shown that the output is “substantially similar” to a copyrighted work and that the AI had access to that work during training. This is difficult to prove. AI companies argue that their models do not “store” or reproduce songs, but instead learn abstract patterns.
Studies cited in copyright debates suggest that fewer than 2% of AI-generated outputs are substantially similar to training data, though critics argue this is likely an underestimate. If courts rule that training itself constitutes infringement, the legal consequences could involve billions—or even trillions—of dollars in liability.
Who Gets Paid?
For fully AI-generated music, ownership is often dictated not by copyright law but by platform terms of service. In many cases, the company providing the AI tool retains commercial rights to the output. This means users may create music but not truly own it.
This raises a critical question: if AI-generated music cannot be copyrighted, who benefits financially? Without clear rules, power may consolidate around large technology companies rather than individual creators.
Possible Paths Forward
There is no single solution, but several proposals are emerging:
- Minimum human involvement thresholds for copyright eligibility
- Short-term or limited copyrights for AI-generated works
- Clear exceptions for educational or research use
- Voluntary licensing agreements, allowing artists to opt in or out of training datasets
- Compensation mechanisms, where artists receive royalties if their work strongly influences AI outputs
Some experts also advocate for self-regulation, where major industry players negotiate standards before legislation catches up.
A Fragile Ecosystem
Ironically, if human creators are pushed out entirely, AI itself faces a long-term problem: without new human-made music, AI has nothing meaningful to train on. Sustainable ownership models are therefore in the best interest of both artists and AI developers.
Ultimately, the question of who owns AI music is not just legal—it is cultural. Ownership determines who is valued, who is paid, and whose creativity shapes the future of music. As the law struggles to keep pace, the decisions made now will define whether AI becomes a collaborative tool—or a force that extracts value without accountability.