First Music Streaming Fraud Case: North Carolina Man Faces Jail and £6.5 Million Fine for Using AI and Bots
Mike Smith exploited AI-generated music and automated streaming accounts, marking the first time law enforcement successfully prosecuted such a scheme.

A North Carolina man has agreed to repay over £6.5 million ($8 million) after pleading guilty in what officials are calling the first-ever criminal case involving AI-assisted music streaming fraud.
Mike Smith, indicted in 2024, used artificial intelligence to generate thousands of songs and then created bots to stream them millions of times, siphoning royalties away from legitimate artists across major platforms.
In addition, he faces a maximum prison sentence of five years for conspiracy to commit wire fraud. There is no indication that he will receive a pardon. Any potential clemency would have to come from the relevant federal authorities, and as of now, the sentence and restitution remain in effect.
How Mike Smith's Scheme Worked
Smith's operation relied on AI-generated music that required no human listeners. Using thousands of fake accounts, he streamed these songs repeatedly on services such as Spotify, Apple Music, and Amazon Music.
According to a summary of the indictment, he earned millions of pounds from streams that were entirely artificial, effectively redirecting royalties intended for real musicians. The activity reportedly amounted to around 660,000 fake streams per day, accumulating roughly £1 million ($1.23 million) per year.
🚨 Do you understand what this man just pulled off..
— Tuki (@TukiFromKL) March 20, 2026
> a guy from North Carolina used AI to generate hundreds of thousands of songs.. uploaded them to Spotify, Apple Music, Amazon.. then botted billions of streams on his own tracks and walked away with $8 million
> 660,000 fake… https://t.co/fuKeyB6gGg pic.twitter.com/ibEUYXJpiB
According to The Hollywood Reporter, US Attorney Jay Clayton commented on the case, stating, 'Smith's brazen scheme is over, as he stands convicted of a federal crime for his AI-assisted fraud.'
Smith pled guilty to conspiracy to commit wire fraud, a charge carrying a maximum sentence of five years in prison, and agreed to return the £6.5 million he earned from the illegal activity.
Impact on the Music Industry
Streaming fraud has long been a concern in the music industry, but AI has significantly accelerated the problem.
Platforms now face the challenge of policing not just fake plays but entire songs that never had a real audience. The French streaming service Deezer reported seeing up to 60,000 AI-generated songs uploaded daily, with around 85 percent of streams for these tracks flagged as fraudulent.
For legitimate artists, the consequences are severe.
Many rely on tiny fractions of revenue per stream while investing heavily in promotion, only to have bots divert funds to synthetic music. As the industry grapples with AI, this first criminal case may set a precedent for future enforcement.
Music Streaming Platforms Respond
Apple Music is cracking down on people who cheat the system by using AI and bots to boost their streaming numbers, raising the penalties for anyone caught. Police and federal authorities are also watching more closely, as AI makes it easier to steal money from real artists.
Even though Mike Smith will pay back all the money he earned illegally, the way he did it is now widely known. This shows the music industry a big warning: AI can create songs and fake listeners at the same time, making it much harder to spot fraud.
Now, the funds will be returned to the US government, which will then work to redistribute the money to the legitimate artists, songwriters, and rights holders whose royalties were siphoned off by his fraudulent streams. Essentially, the repayment is intended to make the music industry whole, compensating those who lost income when Smith's bot-generated streams artificially inflated plays on platforms like Spotify, Apple Music, and Amazon Music.
The process is overseen by the US Attorney's Office for the Southern District of New York.
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