You hit "generate," and thirty seconds later, you've got a fully produced track—vocals, instrumentation, the works. It sounds professional. Maybe even good. But here's the question nobody's quite figured out yet: who actually owns that song?

Welcome to one of the messiest legal puzzles of our time.

The Human Authorship Problem

Here's where things get tricky right out of the gate. U.S. copyright law has a fundamental requirement: human authorship. If a human didn't create it, it can't be copyrighted. Period.

The U.S. Copyright Office made this crystal clear in reports published throughout 2024 and 2025. Music created solely by AI—where you just press a button and walk away—gets no copyright protection. It enters the world as essentially public domain material that anyone can use.

But most AI music creation isn't that simple. You write prompts. You tweak parameters. You regenerate until something clicks. You might layer in your own melodies or adjust the arrangement. This is where the law gets fuzzy.

The Copyright Office says prompts alone don't cut it. Just telling an AI "make me a sad piano ballad" doesn't make you an author, any more than telling a photographer "take a picture of that tree" makes you the photographer. The technology does too much of the creative heavy lifting.

However—and this is important—if you actively shape the output, you might have a claim. Select and arrange AI-generated segments into a larger work? That selection could be copyrightable. Modify the AI's melody or rewrite its lyrics? Those changes are yours. The human contribution needs to be substantial and creative, not just supervisory.

The Training Data Minefield

Now let's talk about the elephant in the server room: what did these AIs learn from?

On June 24, 2024, the Recording Industry Association of America dropped a legal bomb. They sued Suno and Udio, two major AI music platforms, on behalf of Sony, Universal, and Warner—basically the entire major label ecosystem.

The allegation? These companies copied decades of copyrighted recordings to train their models without permission or payment. According to the lawsuits, the AI systems learned from "the world's most popular sound recordings" and now generate outputs that imitate those recordings.

The record labels aren't mincing words. RIAA Chief Legal Officer Ken Doroshow called these "straightforward cases of copyright infringement involving unlicensed copying of sound recordings on a massive scale." The industry fears AI will flood the market with knockoffs that compete directly with human artists.

Musicians are even more pointed. The Music Workers Alliance said AI systems force artists into an unwanted "training role" and create "an inexhaustible supply of knock-offs." The Black Music Action Coalition emphasized that "real music comes from real life and real people" and that training AI on copyrighted music requires permission.

The AI companies face a tough argument. They can't easily claim fair use—the legal doctrine that allows limited use of copyrighted material without permission. Copyright law traditionally protects fair use because it promotes human expression and creativity. But as the RIAA argues, AI-generated music isn't human creativity. It's "imitative machine-generated" content.

The Copyright Office is analyzing this through four factors courts use to evaluate fair use: the purpose of the use, the nature of the original work, how much was used, and the market impact. That last factor looks particularly bad for AI companies if their outputs directly compete with the songs they trained on.

Who Gets What?

So if you make music with AI today, what do you actually own?

Three factors matter most: your level of involvement, the AI platform's training data, and the platform's terms of service.

Your involvement is the biggest factor. The more you do beyond prompting, the stronger your ownership claim. Using AI-generated tracks as raw material, then adding your own melodies, adjusting harmonies, or restructuring arrangements all strengthen your case. Think of AI as a sophisticated instrument or collaborator rather than a vending machine.

Training data issues could bite you even if you do everything right on your end. If the AI learned from copyrighted material without permission, and your output resembles that material too closely, you could face legal challenges—even if you had no idea what the AI trained on.

Terms of service are the fine print everyone ignores but shouldn't. Some platforms claim rights to everything created on them. Others restrict commercial use. Some require attribution. Many prohibit distribution through certain channels. Read the agreement before you release that AI-generated track commercially.

The Documentation Defense

If you're creating music with AI and want to protect your interests, documentation is your friend.

Save everything. Keep different versions of your work. Document what you changed and why. Show your creative process. If a dispute arises, you'll need evidence of your human contribution.

This isn't just paranoia. Copyright disputes often hinge on proving who did what. If you can demonstrate substantial creative involvement—not just prompting but actual musical decision-making—you're in much better shape.

The International Patchwork

Adding another layer of complexity: every country handles this differently.

The U.S. requires human authorship. Other jurisdictions have different rules about AI-generated works, training data, and fair use. If you're distributing music internationally (which, let's be honest, is basically automatic with streaming), you're navigating multiple legal systems at once.

Legislators worldwide are scrambling to address AI training and copyright. Some propose strict licensing requirements. Others favor more permissive approaches. The result is a patchwork of regulations that won't align anytime soon.

What Happens Next?

The lawsuits against Suno and Udio will likely set important precedents. The plaintiffs want three things: declarations that copyright infringement occurred, injunctions stopping future infringement, and damages for past violations.

How courts rule on these cases will shape the entire industry. If judges side with the record labels, AI music platforms will need to license training data—a potentially expensive requirement that could reshape which companies survive. If the AI companies prevail on fair use grounds, we'll see an explosion of AI-generated music with minimal human oversight.

The stakes are genuinely existential. AI advocates warn that requiring licenses will "throttle transformative technology." Artists and labels counter that unlicensed training will "corrode the creative ecosystem" by flooding markets with derivative works that undercut human creators.

The Copyright Office concluded in 2025 that existing law can handle these questions without new legislation. Whether that's true remains to be seen as technology evolves faster than legal precedent.

The Practical Reality

For now, we're in a strange limbo. You can generate music with AI, but you might not own it. The AI platform might not own it either. And if the platform trained on copyrighted material without permission, the whole enterprise might be built on shaky legal ground.

If you're a musician experimenting with AI, treat it as a tool that requires your creative input, not a replacement for creativity. Document your process. Understand your platform's terms. Don't assume that because you can generate something, you own it.

If you're a rights holder worried about AI training on your work, you're not alone—and you're not without options. The legal system is slowly catching up.

And if you're just someone who enjoys music, buckle up. The next few years will determine whether AI becomes a tool that enhances human creativity or a substitute that devalues it. The answer will shape what music sounds like, who gets paid for it, and what it means to be a musician.

The algorithms are already composing. The lawyers are just getting started.