Apple Music Rolling Out Disclosure Tags for AI-Made Songs

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Apple Music is rolling out a new metadata system called Transparency Tags, which indicates when AI has been used in the creation of music hosted on the platform.

According to Music Business Worldwide, Apple sent a newsletter to industry partners on Wednesday to explain how it will roll out the new set of metadata.

The system covers four categories including artwork, track, composition (lyrics), and music video. Labels and distributors can begin applying the tags immediately. Apple describes the tags as optional for now, noting that if omitted, no AI is assumed.

Apple said it defers to content providers to determine what qualifies as AI-generated, and that it treats the tags similarly to genres, credits, and other existing metadata. The company describes it as a first step toward industry-wide transparency around AI-generated music.

Proper tagging of content is the first step in giving the music industry the data and tools needed to develop thoughtful policies around AI,” Apple said in the newsletter, “and we believe labels and distributors must take an active role in reporting when the content they deliver is created using AI.”Apple’s approach contrasts with the route taken by competitors like Deezer, which has built its own detection infrastructure to independently identify AI-generated tracks, but it’s not 100% accurate all the time.

Deezer reports that it receives over 60,000 fully AI-generated tracks per day, with synthetic content now accounting for roughly 39% of all music delivered to the platform. Up to 85% of streams on AI-generated music were fraudulent in 2025, according to Deezer’s data.

With Apple’s tags, there isn’t a visible enforcement or cross-verification process in place. The system is completely voluntary, or at least it is for now. Whether labels and distributors will actually use it remains to be seen.

This article, “Apple Music Rolling Out Disclosure Tags for AI-Made Songs” first appeared on MacRumors.com

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​ Apple Music is rolling out a new metadata system called Transparency Tags, which indicates when AI has been used in the creation of music hosted on the platform.

According to Music Business Worldwide, Apple sent a newsletter to industry partners on Wednesday to explain how it will roll out the new set of metadata.

The system covers four categories including artwork, track, composition (lyrics), and music video. Labels and distributors can begin applying the tags immediately. Apple describes the tags as optional for now, noting that if omitted, no AI is assumed.

Apple said it defers to content providers to determine what qualifies as AI-generated, and that it treats the tags similarly to genres, credits, and other existing metadata. The company describes it as a first step toward industry-wide transparency around AI-generated music.
Proper tagging of content is the first step in giving the music industry the data and tools needed to develop thoughtful policies around AI,” Apple said in the newsletter, “and we believe labels and distributors must take an active role in reporting when the content they deliver is created using AI.”Apple’s approach contrasts with the route taken by competitors like Deezer, which has built its own detection infrastructure to independently identify AI-generated tracks, but it’s not 100% accurate all the time.

Deezer reports that it receives over 60,000 fully AI-generated tracks per day, with synthetic content now accounting for roughly 39% of all music delivered to the platform. Up to 85% of streams on AI-generated music were fraudulent in 2025, according to Deezer’s data.

With Apple’s tags, there isn’t a visible enforcement or cross-verification process in place. The system is completely voluntary, or at least it is for now. Whether labels and distributors will actually use it remains to be seen.Tag: Apple MusicThis article, “Apple Music Rolling Out Disclosure Tags for AI-Made Songs” first appeared on MacRumors.comDiscuss this article in our forums   Read More MacRumors: Mac News and Rumors – All Stories 

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