Man jailed for using 1,000 bots to fraudulently make $8m from his AI music

Smith uploaded hundreds of thousands of AI-generated songs to Spotify, Apple Music, Amazon Music, and other services. He then used automated accounts to create fake streams. The scheme lasted from 2017 to 2024 and made his music appear far more popular than it was. That matters because royalties were paid based on fraudulent activity.

The operation used 52 cloud-service accounts, each connected to 20 bots, giving Smith 1,040 AI agents. The Justice Department said he sometimes deployed up to 10,000 bots. His tracks were played billions of times, including 80.9 million YouTube Music plays in April 2023. He earned $8,091,843.64.

Smith was charged in September 2024 and pleaded guilty to one conspiracy count in March 2026. He was sentenced to 18 months in prison, followed by two years of supervised release. He must also forfeit all $8,091,843.64 from the scheme.

Streaming fraud is the deliberate use of fake activity to manipulate music-play counts and obtain money. A platform may treat a stream as evidence that someone listened to a track. When automated accounts generate those plays instead, the numbers no longer represent real consumer demand. The inflated figures can influence royalty payments and make unknown music look successful.

Smith uploaded huge numbers of songs and used bots to stream them repeatedly. His bots could produce roughly 636 songs per day each, according to the article’s account. The Justice Department said his music received 80.9 million YouTube Music plays in April 2023, far exceeding Taylor Swift’s 9.3 million plays there that month.

The harm goes beyond misleading charts or recommendations. Fraudulent plays divert money from legitimate musicians and songwriters whose work was actually streamed. Smith’s case shows how AI can make mass music production easy, while automated engagement can turn that output into a criminal scheme.

Smith’s operation was unusually large because it combined mass uploads with automated listening. He placed hundreds of thousands of songs on major platforms, then directed bots to play them repeatedly. The article says the activity ran from 2017 to 2024 and generated billions of plays. That scale helped convert fake popularity into substantial royalty payments.

One account described 52 cloud-service accounts, each with access to 20 bots. That gave Smith 1,040 bots, capable of around 661,440 daily plays based on 636 songs per bot. The Justice Department gave an even higher estimate, saying he deployed as many as 10,000 bots at once. In April 2023, his music received 80.9 million YouTube Music plays.

The operation generated more than $8 million across various platforms. A court ordered Smith to forfeit $8,091,843.64. The figures show that streaming manipulation can operate at industrial scale, even though ordinary AI-generated tracks generally receive little genuine engagement.

Music-streaming platforms commonly use listening activity to determine how recorded-music revenue is distributed. In simple terms, a track with more eligible streams can receive a larger share of the money available for royalties. The article refers to platforms’ per-stream payment plans, but it does not give one universal rate or explain every platform’s formula.

Smith targeted this system by sending bots to play his songs repeatedly. The artificial streams increased his tracks’ apparent usage, so the platforms treated them as activity that could generate payments. He uploaded music to Spotify, Apple Music, Amazon Music, and other services, seeking royalties from the inflated numbers.

The system is not a guaranteed fixed price for every play. Rates and rules vary by platform, and real-world payments depend on each service’s arrangements. Still, the basic vulnerability is clear: if automated plays are counted like legitimate listening, fraudulent users can claim money that would otherwise go to genuinely streamed music.

Cloud accounts gave Smith a way to control many automated agents at once. The article says 52 accounts each had access to 20 bots, creating 1,040 bots. VPN connections can route activity through different network addresses, making repeated streams harder to link immediately to one location or device. That helped support the appearance of distributed engagement.

The bots streamed roughly 636 songs per day, according to the article’s account. Together, 1,040 bots could produce about 661,440 daily plays. The Justice Department said Smith sometimes used as many as 10,000 bots. These systems allowed him to repeat plays at a volume no ordinary listener could achieve.

The setup did not make the activity legal or genuinely authentic. It simply helped create the appearance of many independent listeners and produced huge numbers for payment purposes. The eventual investigation and prosecution show that technical disguise cannot turn automated engagement into legitimate consumer demand.

Royalty pools are meant to reward music that attracts legitimate listening. When bots create fake plays, fraudulent tracks can claim part of the money associated with streaming activity. That leaves less available for artists and songwriters whose songs were played by real consumers. The Justice Department described this as diverting funds from legitimate creators.

Smith’s scheme shows the mechanism clearly. His bots produced billions of artificial plays, including 80.9 million YouTube Music plays in April 2023. Those numbers made his tracks appear more successful than they were and helped generate more than $8 million. The money came from platforms’ per-stream payment arrangements.

Legitimate artists can therefore lose both income and visibility. False engagement may affect how platforms interpret popularity, while genuine musicians compete against manufactured numbers. The article also notes that more than a third of Apple Music’s tracks were described as fully AI, yet they received below 0.5% of usage, showing how limited real attention can be.

Creating a song with AI is generally different from making a false claim about how many people listened to it. The article states that Smith was not prosecuted for producing AI-generated music. Instead, he was prosecuted because he used automated engagement to misrepresent popularity and obtain royalties. The legal issue was deception and financial gain, not the production method.

Smith uploaded hundreds of thousands of AI-generated tracks and used bots to stream them billions of times. Those plays made the music appear popular and triggered payments under streaming platforms’ per-stream plans. Prosecutors charged him with wire fraud conspiracy, wire fraud, and money laundering conspiracy. He ultimately pleaded guilty to conspiring to commit wire fraud.

The distinction matters as AI makes music faster and easier to produce. The article says more than a third of Apple Music tracks were fully AI, but they received below 0.5% of usage. Future enforcement is therefore likely to focus on artificial engagement and monetization, rather than AI music creation alone.