Man Pleads Guilty to Making $8 Million by Creating Music With AI and Using Bots to Drive Zillions of Fake Streams

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For quite some time now, human musicians have watched in horror as AI-generated slop has started drowning out their work on streaming platforms.

Companies like Spotify have discovered entire networks of bots that were designed to fraudulently boost the listenership of AI-generated music, a bizarre scheme essentially involving bots listening to bot music to capture royalties that could’ve otherwise been paid out to real human artists.

The problem has been around for years — but prosecutors are finally catching onto the dubious scheme and putting those running the bot farms to justice.

In a Department of Justice press release, the Southern District of New York attorney Jay Clayton announced that North Carolina native Michael Smith had plead guilty for creating “hundreds of thousands of songs with AI” and using “automated programs called ‘bots’ to fraudulently stream his AI-generated songs billions of times.”

The goal was to “mimic the genuine streaming activity of real consumers,” ultimately allowing him to “fraudulently obtain more than $8 million in royalties” across music streaming platforms such as Amazon Music, Apple Music, Spotify, and YouTube Music.

Smith pled guilty to one count of conspiracy to commit wire fraud, and is facing a maximum of five years in prison. His sentencing has been scheduled for July 29. Smith has also agreed to forfeit over $8 million he made on the scheme.

“Although the songs and listeners were fake, the millions of dollars Smith stole was real,” said Clayton in a statement. “Millions of dollars in royalties that Smith diverted from real, deserving artists and rights holders.”

“Smith’s brazen scheme is over, as he stands convicted of a federal crime for his AI-assisted fraud,” Clayton added.

The news highlights how AI tools aren’t just being used to impersonate artist; the tech is being used to generate phony listenership as well, through both armies of bots and unassuming listeners.

According to the press release, Smith’s payout was actively taking away from a singular “pool of funds” that could’ve gone out to “musicians and songwriters whose songs were legitimately streamed by real consumers.”

A Rolling Stone investigation into Smith published earlier this year found that the “suburban dad in his forties who owned a chain of urgent-care facilities,” was running 1,040 accounts across streaming platforms, each one streaming around 636 songs each day. According to Smith’s own estimates, he was earning roughly $3,300 a day, or over $1.2 milion a year.

While some of his songs were created by real musicians who were often not credited, per Rolling Stone, many other songs were fully AI-generated.

Smith was arrested at his home outside of North Carolina in September 2024 and initially denied any wrongdoing.

Beyond fraudulent schemes involving armies of listening bots, the use of AI on music streaming platforms has become a lightning rod. We’ve come across entirely AI-generated bands racking up millions of listens on Spotify, Apple Music and YouTube Music.

High-profile artists, like Aubrey “Drake” Graham, have found that their voices were being deepfaked for viral tracks that they had nothing to do with as well.

Spotify has since attempted to address the issue by coming up with new policies that forbid impersonation and establish common “AI disclosures in music credits.”

The company also claims to be investing “heavily in detecting, preventing, and removing the royalty impact of artificial streams.”

While the latest news suggests there’s at least some momentum in bringing perpetrators abusing music streaming platforms to justice, it remains unclear whether companies like Spotify have been able to meaningfully address the bot problem.

It’s a persistent game of cat and mouse that’s making it even more difficult for small artists to stand out as their work continues to be drowned out by AI slop.

More on AI music: The AI-Generated Tilly Norwood Just Dropped the Worst Music Video We’ve Ever Seen