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AI Music Is Appearing on Spotify—and Fraudsters Can Use It to Divert Royalties

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Yes, Spotify hosts AI-generated music, and there is documented evidence that fraudsters have paired AI-made songs with fake streams to collect royalties. But that is not proof Spotify itself is filling the service with AI music or that most AI tracks are scams. The clearer concern is third-party operators using cheap production, misleading artist identities, stolen or misattributed uploads, and artificial listening to exploit streaming’s royalty system.

“AI music” can mean several different things

A song made with AI is not automatically fake, fraudulent, or even mostly machine-made. The phrase can describe a fully synthetic track generated from prompts; a human-written song with AI-assisted vocals, instruments, mixing, or mastering; an AI cover; or a virtual performer presented as an AI persona. Those are different from an unauthorized voice clone, a human recording uploaded under the wrong band’s name, or an invented artist profile used to disguise who controls a release.

There is also conventional functional music—ambient, sleep, or background tracks—uploaded at scale. That business model predates generative AI. AI can make it cheaper to produce more of it, but volume alone does not show that a track is deceptive or that it has attracted listeners.

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Spotify’s stated concern is harmful conduct such as spam, impersonation, and artificial streaming, not simply the use of AI in production. Its AI protections announcement describes work on voice impersonation and fraudulent delivery to artist profiles. AI-assisted work can still involve substantial human authorship; a synthetic sound is not, by itself, evidence of a scam.

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How fake streams can take money from legitimate artists

Spotify’s royalty system is generally described as pro rata: eligible streams determine each track’s share of a pool, rather than each subscriber’s payment going only to the artists that subscriber played. Spotify says roughly two-thirds of its music revenue is allocated to recording and publishing royalties, with the allocation divided approximately four-fifths to recording rights and one-fifth to publishing. The amounts individual performers receive depend on rights ownership and their agreements with labels, publishers, and distributors. Spotify’s royalty guide explains why there is no single universal per-stream rate.

A basic fraud chain can look like this:

  1. An operator uses inexpensive tools to generate or assemble many tracks.
  2. The operator delivers them through a distributor, perhaps under invented artist identities or a name that resembles a real act. In other cases, a release is wrongly attached to an existing artist profile.
  3. The operator arranges artificial streams, or tries to use early activity to gain exposure.
  4. If the plays count as eligible streams before detection, the tracks can claim a larger share of the pool.
  5. The operator tries to collect the resulting royalties before the activity or account is stopped.

That is dilution of a shared pool, not necessarily a direct transfer from one named band to one fake act. Spotify says artificial streams dilute royalties by shifting the pool toward bad actors. It says confirmed artificial streams do not earn royalties and can lead to stream corrections, playlist removal, distributor penalties, account suspension, or takedowns. Spotify’s artificial-streaming guidance and warning about paid services promising streams spell out the risks.

AI can act as an industrial multiplier: it makes it faster and cheaper to produce genre-specific tracks, variants, artwork, and plausible artist packaging. It may also help operators imitate familiar sounds or exploit playlist keywords. But streaming fraud, fake identities, stolen recordings, and playlist manipulation existed before generative AI. The technology increases the scale and lowers the cost; it did not invent the incentive.

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A criminal case shows the model is real—not how common it is

The strongest concrete example in the dossier is the U.S. case involving Michael Smith. Prosecutors said he generated thousands of songs with AI and used bots to stream them billions of times, producing more than $8 million in royalties. Reports on the case include coverage of his guilty plea and Bloomberg Law’s report.

This demonstrates that AI-generated music can be part of a large royalty-fraud operation. It does not establish that most AI tracks on Spotify are fraudulent, measure what share of Spotify’s catalog is synthetic, or show that Spotify organized the scheme. The distinction matters: a documented crime proves a method was used, not its prevalence across a platform.

Impersonation and hijacked profiles are a separate risk

Not every suspicious release is a fully synthetic song. A bad actor may upload a human recording without permission, use a confusingly similar artist name, or get a track attached to a real band’s profile. An AI-generated voice or cover can raise additional questions about consent and rights, but the audio may also be entirely human-made while the identity or upload is fraudulent.

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Reporting has described an AI-generated band receiving roughly a million Spotify plays and musicians confronting tracks uploaded under their names. See The Guardian’s reporting on AI impersonation and Philadelphia Magazine’s account of music and bot-streaming concerns. Such reports illustrate possible harms: confusion for listeners, lost visibility, time spent seeking takedowns, and potential dilution of royalties. They are case studies, not a count of all affected artists.

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Nor does a recommendation, playlist placement, or unfamiliar artist profile prove a track is fake. Automated systems can surface material based on listener behavior, similarity, metadata, or early engagement. A profile that looks odd is a reason to check, not a verdict about the people behind it.

Large upload counts do not equal large audiences

In September 2025, Spotify said it had removed more than 75 million “spammy tracks” in the preceding 12 months. That is Spotify’s own enforcement figure, and its wording is important: it did not say 75 million AI-generated tracks. The company has not provided a breakdown in the cited material showing how many removals involved AI, bot streams, impersonation, or other forms of spam—or how much money was recovered.

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A 2026 empirical preprint, “An Empirical Analysis of AI Slop in Music Streaming,” reported that 93% of the AI tracks it identified received few or no plays and were rarely recommended. The finding is a useful counterweight to claims that a flood of uploads means a flood of listening. It is not necessarily representative of every Spotify upload, and “few or no plays” does not show that no smaller subset has obtained meaningful exposure or artificial streams.

Keep five measures separate: catalog volume, audience reach, artificial consumption, royalty impact, and platform economics. A large number of uploads tells us little by itself about how many people heard them or how much money was diverted. Spotify says it paid more than $11 billion to the music industry in 2025, but that overall payout figure does not disclose the scale of AI-related fraud. The payout announcement is a company-reported industry total, not an audit of suspicious royalties.

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A Duke Sanford policy paper argues that AI music and bot streaming expose weaknesses in pro-rata royalties. Any diversion estimates in policy analysis should be read as analysis or modeling, not independently audited Spotify accounting. The available evidence supports that artificial streams can dilute the pool and that at least one large operation exploited the system; it does not provide a comprehensive total for money diverted by AI-related fraud.

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What Spotify says it is doing—and what remains unclear

Spotify says it is pursuing spam removal, artificial-stream detection, protections against unauthorized voice impersonation, and ways to address fraudulent releases delivered to an artist’s profile. It also announced collaboration with music companies on responsible AI uses, including a major-label AI initiative and, with Universal Music Group, licensed covers and remixes. These initiatives point to an approach that combines enforcement with authorized experimentation, rather than a blanket ban on AI-made music.

Reports in 2026 described Spotify introducing “AI Persona” labels or badges on artist profiles. TechRadar, MusicRadar, and What Hi-Fi reported on the feature. These are secondary reports; rollout, geographic availability, eligibility, exact wording, and visibility to listeners should not be assumed to be universal.

An artist-persona label is also not the same as labeling each recording. It may identify an AI persona without explaining whether a specific track is fully synthetic, AI-assisted, or made by people using a virtual project identity. A label does not by itself establish that streams are fraudulent, prevent recommendations, or stop royalties from being paid. Spotify has not publicly disclosed, in the cited sources, how many AI-related tracks it removes, how much suspicious money is withheld or recovered, how often mistaken flags are reversed, or how widely persona labels are shown.

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Spotify’s position also deserves a fair description: it says it does not create or own the music uploaded to its service, and that tracks are treated equally regardless of the tools used to make them. Uploaders and rights holders generally deliver music through distributors. That does not settle whether Spotify’s safeguards are sufficient, but it is different from saying the company itself is producing fake bands to steal from artists. A claim of deliberate platform orchestration would require evidence beyond the cases and policies cited here.

What artists can do if a release or stream pattern looks wrong

  • Monitor your catalog and activity. Use Spotify for Artists to keep track of releases, profile changes, audience data, and unusual activity. It does not guarantee immediate control over impersonating uploads or suspicious streams.
  • Search your artist name periodically. Check for unfamiliar tracks, confusingly similar profiles, or releases attached to the wrong page. Treat visual oddities, fast release schedules, and synthetic-looking artwork as leads rather than proof.
  • Preserve evidence before it disappears. Save URLs, screenshots, release dates, distributor notices, relevant metadata, and a record of unusual stream patterns. Keep original recordings, project files, artwork, and release documentation where available.
  • Contact your distributor and use Spotify’s reporting channels. Distributors often handle delivery, metadata correction, and takedown requests. Explain whether the issue is an unauthorized recording, profile misattribution, voice imitation, or suspected artificial streaming; those are not identical complaints.
  • Do not buy guaranteed streams. Spotify warns that paid services promising streams violate its terms and may lead to withheld royalties, corrected numbers, playlist removal, or other consequences. An artist can also be affected by suspicious activity they did not arrange, so a flag is not proof of guilt.
  • Tell fans through verified channels if needed. If an unauthorized release is causing confusion, point listeners to your verified profile and share factual information without accusing another artist or operator unless you have evidence.

Listeners do not need to treat every AI label—or every unfamiliar artist—as a warning of criminal conduct. If a profile appears to impersonate an act or a release is plainly misattributed, report it through Spotify rather than amplifying an unverified accusation.

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