A North Carolina man has been sentenced to 18 months in federal prison for orchestrating an AI music royalty fraud scheme that prosecutors say generated more than $8 million through billions of artificial streams. The case highlights a growing challenge for the music industry as generative artificial intelligence makes it easier to produce music at scale, while automated accounts can manipulate streaming systems designed to reward genuine listener activity.
Michael Smith, 54, received his sentence in federal court in Manhattan after pleading guilty to conspiracy to commit wire fraud. In addition to his prison term, he was ordered to serve two years of supervised release and forfeit $8,091,843.64, according to the U.S. Attorney’s Office for the Southern District of New York.
The case is notable not simply because of the amount of money involved, but because it demonstrates how AI-generated music and automated streaming can be combined to exploit the financial systems supporting artists, songwriters and other rights holders.
How the $8 Million AI Music Royalty Fraud Worked
According to federal prosecutors, Smith operated the scheme from 2017 through 2024. The operation relied on three interconnected elements: large volumes of AI-generated music, thousands of fraudulent streaming accounts and software that repeatedly played tracks to generate royalty payments.
Instead of building an audience through promotion or attracting listeners organically, Smith allegedly manufactured the appearance of widespread demand. The streams were automated, meaning the activity did not reflect genuine people choosing to listen to the music.
Thousands of Bots and Hundreds of Thousands of Songs
Prosecutors said Smith created thousands of accounts on music streaming services using fake email addresses and debit cards obtained through fraudulent means. He then used software to play music he owned, much of which had been generated using artificial intelligence.
At its peak, the operation allegedly ran as many as 10,000 bot accounts simultaneously. Rather than concentrating the activity on a small number of tracks, Smith spread the streams across thousands of songs.
This approach was intended to make the listening patterns less conspicuous to automated fraud detection systems. A single song receiving an extraordinary number of plays might attract immediate scrutiny. Distributing those plays across a vast catalog, however, could make suspicious activity harder to identify.
The scale of the operation depended on producing enough music to sustain the artificial listening activity. In an email cited by prosecutors, Smith reportedly said he needed “a TON of songs fast” to circumvent streaming platforms’ anti-fraud policies.
By June 2019, Smith and his alleged co-conspirators were reportedly earning approximately $110,000 per month in royalties from hundreds of thousands of tracks.
How Fake Streams Divert Money From Real Artists
The scheme exploited a fundamental feature of the streaming economy: royalty payments are generally calculated through arrangements that distribute revenue among rights holders based on listening activity and contractual terms.
Although the precise calculations vary by platform, territory, subscription type and licensing agreement, streams can influence how money is allocated to artists, labels, publishers and songwriters.
Why Streaming Fraud Hurts Musicians
Streaming services do not necessarily pay every artist a universal, fixed amount for each play. Instead, many services use revenue-sharing models in which eligible listening activity helps determine how royalty pools are distributed.
When fraudulent streams enter that system, they can distort the calculations used to allocate money.
For example, if automated accounts generate millions of artificial plays for music that nobody genuinely wants to hear, the resulting royalty claims may divert revenue from legitimate rights holders. Independent musicians can be particularly vulnerable because streaming income often represents one of several limited sources of revenue available to them.
The problem extends beyond lost payments. Fake activity can also undermine streaming statistics, distort popularity rankings and make it more difficult for platforms to distinguish emerging artists from manipulated catalogs.
For musicians who spend years building an audience, the prospect of competing against artificially inflated listening figures presents a serious concern.
The Scale of the Fraud Surpassed Major Artists’ Listening Figures
One of the most striking details in the prosecution involved a comparison with Taylor Swift’s music catalog.
According to the Justice Department’s announcement, family-plan listeners streamed Swift’s entire catalog 9.3 million times on YouTube Music in April 2023. During that same month, Smith’s bot accounts allegedly generated 80.9 million streams for his AI-generated music.
The comparison illustrates the extraordinary scale of the operation. A catalog controlled by one of the world’s most successful recording artists received substantially fewer streams in the cited comparison than the artificial activity attributed to Smith’s operation.
Ultimately, prosecutors said the scheme generated more than $8 million in royalties.
U.S. Attorney Jamie McDonald condemned the operation, arguing that replacing genuine listeners with automated bots and real artistic output with fabricated songs diverted money from legitimate artists.
The Department of Justice characterized the case as the first criminal prosecution of a music streaming fraud assisted by what it called “super intelligence” technology. Its announcement did not specify the AI tools Smith used, so the exact systems involved remain unclear from the information released.
AI-Generated Music Raises New Questions for Streaming Platforms
Artificial intelligence is changing how music can be composed, produced and distributed. Generative tools can help musicians experiment with arrangements, develop ideas and create recordings more efficiently. They can also produce large quantities of content with comparatively little manual production work.
That accessibility creates legitimate creative opportunities. However, it also introduces risks when people use automation to manipulate systems that reward listening activity.
The distinction is important: AI-generated music is not inherently fraudulent. The central issue in Smith’s case was the alleged combination of artificially generated tracks, deceptive accounts and automated streams used to obtain royalties.
Streaming platforms must therefore balance two competing priorities. They need to accommodate legitimate AI-assisted creativity while preventing users from exploiting their royalty systems.
Potential safeguards include stronger account verification, improved detection of abnormal listening patterns, closer examination of suspicious royalty claims and better coordination between streaming services and rights holders. Yet fraud detection is an ongoing challenge because bad actors can adapt their methods as platforms strengthen their defenses.
For services handling billions of streams, identifying coordinated manipulation requires more than examining the popularity of individual songs. Platforms may also need to assess relationships between accounts, unusual listening behavior and broader patterns across large catalogs.
Billions in Potential AI Music Revenue Losses Raise Industry Concerns
Smith’s prosecution comes amid wider concerns about the economic impact of AI-generated music.
A study by the International Confederation of Societies of Authors and Composers (CISAC) and consultancy PMP Strategy, with participation from French streaming service Deezer, estimated that annual revenue losses for artists could reach approximately $4.6 billion by 2028 because of AI-generated music.
That projection concerns a broader industry issue and should not be interpreted as a measurement of losses caused by Smith’s operation alone.
Nevertheless, the estimate underscores the financial stakes as AI-generated content becomes more widespread. Questions about copyright, consent, attribution and royalty allocation are increasingly central to discussions about the future of recorded music.
The industry must also distinguish between legitimate AI-assisted releases and content designed primarily to exploit payout mechanisms. Effective policies will need to protect artists without unfairly penalizing musicians who use emerging technologies as part of an authentic creative process.
What the Sentence Means for the Future of Music Streaming
Smith’s 18-month prison sentence, two years of supervised release and forfeiture order send a clear message about the legal risks of manipulating digital music royalties through fraudulent activity.
The case also demonstrates why streaming integrity has become an important issue for the wider music business. As production tools become more accessible, platforms face increasing pressure to ensure that royalty payments reflect legitimate listening rather than automated manipulation.
For artists, labels and songwriters, protecting that integrity is essential to maintaining confidence in the streaming economy. For platforms, the challenge is to improve fraud prevention without restricting legitimate experimentation with new creative technologies.
Ultimately, the $8 million AI music royalty fraud case is a warning about the consequences of exploiting digital distribution systems. Artificial intelligence may change how music is made, but the financial systems supporting the industry still depend on trustworthy data, transparent practices and meaningful protections for the people who create the music audiences choose to hear.