Suno: Bad for Music, Bad for AI.

Imagine a world without Suno.¹ It’s easy! Easy for me, anyway—I’ve never logged on. As a matter of policy, I won’t use generative AI music creation tools that aren’t trained on an opt-in, transparent, licensed, and compensated model. As a musician and music rights advocate, that’s a value I prioritize.

Others would feel a great loss without Suno—I know this because I’ve spent time lurking in the r/SunoAI subreddit. I read it because I want to understand how and why people use it. Its users are passionate—some claim to listen to their own prompted Suno music exclusively. I’ve read posts from dozens of AI music creators whose lives have been enriched by Suno, who feel part of a community, and in some cases feel oddly superior to human artists who have wasted so much time developing old-fashioned skill sets like singing, songwriting, playing instruments, and recording music.

I know from the conversations I have every day that many of us in the creative music communities resent and regret Suno’s launch. Compare Suno’s origins to Spotify. Spotify had its origins in an illegal pirate platform, but it ostensibly launched with licenses in hand from all necessarily rights holders. I signed up for Spotify when it launched because I thought it would be a value add in my life. It has been, but I’ll only continue to support Spotify if I continue to believe it’s a value add for music. Honestly, the jury’s out—but at least they got permission and paid for the music.

I’ve been consistent in my fierce objection to what I consider Suno’s original sin of training its model on tens of millions of scraped tracks and launching a commercial product without any licenses. As a music lawyer I regard this act as an egregious violation of intellectual property laws.²

It’s evident that Suno’s rush to market without permission, licensure, or compensation has polarized the music community and often galvanized creative communities into hardened “anti-AI” positions. This reflects a much larger trend in technology, culture, and politics; but it’s feeling like battle lines are drawn. It didn’t have to go down like that.

As an artist advocate, I’ve looked at these issues through the lens of impacts on artists and artist communities. I’ve tried to keep a balanced view, while processing my own emotional reactions around Suno’s wrecking ball entrance into the market. I want to keep my opinions balanced and nuanced for the benefit of my clients; but it often feels like a gut punch when I see how all these important participants—musicians, singers, songwriters, producers, engineers, labels, and publishers—are economically harmed by the outcomes.

Last week my law firm co-sponsored a conference with the Indiana University Jacobs School of Music and Mauer School of Law called Algo Rhythms: Exploring Human-Centered Creativity in Music and AI.

I spoke on a panel on legal frameworks, which focused on copyright and other personal rights. It was a nuanced discussion that acknowledged the actual and potential value of AI, but emphasized the risks and harms of prompt-created commercial music currently flooding the market and the cavalier attitudes of those responsible.

After my panel, I met Marcus Lawrence, an AI music journalist who publishes the newsletter Zinstrel. His review of the conference gave me a new perspective. The TL/DR is that Marcus is frustrated because so many of us remain laser focused on Suno as a bad actor, which distracts from a larger conversation about how AI tools can empower creative individuals.

Without absolving Suno for its “move fast and break things” ethos, Lawrence expressed frustration that Suno’s problematic and divisive launch had become the entire conversation. His take made me rethink my own position. Maybe AI isn’t the problem, but rather Suno’s aggressive and likely illegal entrance and push for market domination is the problem. Maybe Suno isn’t just harming music, musicians, and music professionals; maybe Suno has harmed the future of AI music as an institution.

When I write about issues I have with AI music, I always note that I’m not anti-tech or even anti-AI. For the most part I’m a tech optimist. I use AI tools. I have no issue with anyone using fairly trained AI tools for music applications. Whether it’s post-production, instrument modeling, algorithmic marketing, or idea generation, AI has many good use cases associated with music and music production. If it’s a generative model with licensed training data and outputs that are somehow differentiated from human-made music, no problem. If we can create efficiencies and empower creators without cutting jobs, stealing or devaluing property, or destroying the environment, then I’m generally OK with it.

Suno entered the music market like a bull in a china shop. Musicians had strong opinions, mostly negative. The hype cycle followed. Mainstream producer Timbaland became a strategic advisor, calling Suno the “future of music production.” Later that year a fictional classic rock-style “band” was “exposed” as an Suno-created project. Every music publication and even some mainstream publications showed the strange, AI-generated “band photos” of ghostly, mismatched young men in awkward hippie outfits.

Then 2025 saw a string of chart hits. First, a mysterious country act called Breaking Rust had a number one single. Then a big-voiced R&B/gospel singer named Xania Monet had a radio hit. It was all happening so fast.

Here’s the thing. None of these news items amounted to anything the music industry would consider successful. The Velvet Sundown was purely a hype cycle. Their audience is nonexistent. Breaking Rust had a number one hit on Billboard’s digital songs chart. That position reflects a few thousand iTunes sales. It’s probably worth buying a few thousand tracks for around a dollar a piece to get a headline. And Monet—the biggest AI act in the world—currently has fewer than a million monthly listeners on Spotify. The song “How Was I Supposed to Know” debuted at number thirty on the Billboard Adult R&B Airplay Chart—which is significant, but not conclusive evidence of actual success. Monet is the best anyone has done to date.

I recognize that the majority of people don’t give music all that much thought. Some of us, however, care very deeply about music. I don’t just mean musicians and people in the business; I mean people who are truly passionate about music, who have well-defined musical taste, who experience deep joy in the music they love. Music people can’t imagine life without great songs, great voices, great records—they won’t accept a knockoff of the music they truly love.

The Velvet Sundown was like a Rorschach test. Some people saw it as the end of music, the moment the machines took over. Others like me found it laughably bad. There weren’t many opinions in the middle. But after the story died down, nobody listened. Now the breakout song has fewer than five million streams. Turns out the people who thought it sucked were the people they needed to win over. Those impressed by the recording quality or the similarity to classic rock records weren’t going to be the return listeners. A real audience develops when people connect with the music on an emotional level.

People don’t reject this music simply because it’s AI; they reject it because it lacks the emotional resonance people seek in the music they choose.

Suno is bad for the future of AI music because it blew its entrance. with tens of millions of slop tracks on services in addition to the competitive releases such as Monet and Breaking Rust, you’d expect to have something break out. Promoters of AI music have put in the effort. They took a big bet, spent a lot of money, and failed. Now the majority of people not only hate AI music, they hate the very idea of AI music. They want to know it’s real human music so they don’t waste their time on something inauthentic. Where does that leave us?

There’s no question that Suno has facilitated streaming fraud at scale. Tens of thousands of inferior, prompt-created tracks are uploaded to services every day, diverting and diluting the royalty pool for human artists. Spotify recently deleted 75,000,000 “spam” tracks from its platform—that’s almost as many tracks as there were on Spotify in 2019. There’s been such an acceleration of uploads in the past couple years that we don’t even notice a block deletion of nearly half the catalogue. That’s a crisis.

I got myself in trouble in my panel talk by noting songwriter demos as a reasonably legitimate use case. Professional publishers and songwriters pointed out all sorts of things that are problematic with Suno demos. Songwriters are horrified when their publishers create Suno demos from their work tapes. Suno makes mistakes, screws up melodies, misses chord changes, and the vocals sound weird. Even more disturbing is the uncertainty of how Suno uses the songs that are uploaded. Do those unreleased songs become training data? The most recent version of Suno encourages users to upload their own voice to create an AI facsimile. Do they own that as well?

The sync (film and television) business has become self-policing against AI music. All the major sync houses and streaming services have anti-AI policies as a defensive position. Voluntary labeling will likely scale because nobody wants to be mistaken for AI music. Companies like Humanable are offering to certify tracks as substantially AI-free, which I predict will become a badge of honor in certain music cultures.

It’s a common claim that people can’t tell the difference between AI and human music. AI music “sounds professional,” therefore it’s “as good as” human music. The problem is that “professional” sound has become extremely processed as digital technologies have developed.

We’re used to hearing everything tuned and tidied up to the point where human mistakes that have been largely eliminated. It may sound like professional music, but professional sound is cheap and accessible. Sounding good doesn’t mean music has the qualities music fans seek. It’s impossible to quantify, but we know it when we hear it. You don’t need science to prove this point when we’ve already rejected everything the industry has to offer by simply choosing not to listen.

Generative models improve through access greater volume and quality of training data. With multiple lawsuits and negotiations on limiting access and adding cost to its access to training data, I don’t see how their model improves in its ability to mimic quality music.

According to its CEO, Suno seeks to make music-making to be more like playing video games. Remember when Guitar Hero blew up? People want to passively enjoy music, and I don’t fault them. Music-making as a passive consumer experience is fine—as long as it’s within a legal framework that doesn’t devalue existing music to take away from working musicians.

Actual musicians find joy in the process. We want it to be less like video games—less isolating, fewer screens, more community. We record in analog studios because we want to get off screens. We make music together in person because it’s about human connection, not isolation. I believe the next innovators—the true geniuses of AI music—will create and train their own tools for their own purposes to leverage and enhance creativity.

The future of music creation belongs to creative individuals, not algorithms. The sooner we embrace that, the sooner we can get back to making the most amazing music anyone’s ever heard. That future is ours if we can find our way through this dark period caused by the unrestrained greed and malfeasance of technologists who don’t even understand the product they are selling.

1. Udio too - just keeping this simple since Suno is still up to its bullshit.

2. Suno has claimed its actions are protected under Fair Use; however, it is actively defending multiple infringement suits, including those brought by Sony and Universal Music Group.