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Spotify Removes More Than 50 Million Spam and Slop Tracks From Recommendations

The 2026 figure counts tracks excluded from recommendations. An earlier total of more than 75 million refers to spam tracks removed from the platform itself.

Headphones beside a phone with a sparse grid of music covers / TokenPost.ai
Headphones beside a phone with a sparse grid of music covers / TokenPost.ai

More than 50 million tracks classified as slop or spam have been removed from Spotify’s recommendations so far in 2026, following changes designed to give human artists more visibility.

The figure measures tracks kept out of recommendations, not tracks necessarily deleted from Spotify. It combines slop and spam classifications and does not establish how many of the tracks were AI-generated.

Over the past six months, Spotify has adjusted its recommendation system using signals including listener behavior and feedback, upload patterns, track information and third-party AI detection tools. Its editors also leave material identified as slop or spam out of their selections. AI detection has limits as generative tools develop.

The changes build on a music spam filter announced in September 2025. That filter was designed to identify tactics such as mass uploads, duplicate tracks and artificially short songs, then stop recommending affected music.

Spotify has also labeled thousands of artist profiles with AI Persona badges. Music from those profiles is generally excluded from editorial and algorithmic recommendations, though following a profile can make its music eligible for a listener’s recommendations. The badge describes the artist’s presented identity; it does not indicate how any particular song was made.

Artists can separately disclose AI use in a song’s creative process through AI Credits, which appear in Song Credits. That disclosure serves a different purpose from the profile badge.

An earlier total of more than 75 million spam tracks covered removals from Spotify’s platform over the 12 months before Sept. 25, 2025. Those platform removals and the 2026 recommendation exclusions measure different actions during different periods.

John Kim

John Kim reports on the digital-asset business for TokenPost. Send corrections or tips to info@tokenpost.com.

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