Apple Music will soon start labeling AI-generated music

When Apple Music informed its industry partners that incoming releases featuring a material portion of artificial intelligence must carry a Made with AI label, the directive relied entirely on an honor system. Set to roll out later this year, the policy follows an earlier push in March when Apple introduced transparency tags for music distributors, a shift that arrives as streaming platforms and independent artists diverge sharply over how to police automated tracks.

The stakes of that division are already playing out globally. In Kathmandu, artists and label owners have discovered unauthorized AI-generated covers and voice clones of their original compositions circulating on major platforms without automated notification, forcing creators to police their own catalogues manually.

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Apple Music vice president Oliver Schusser recently revealed that more than a third of the tracks uploaded to the platform are entirely AI-generated. Despite that volume, Apple is not deploying machine learning detection tools to catch unlabeled uploads. Instead, the company stated that content providers are best positioned to know how their content was created, leaving compliance entirely in creators' hands, according to reporting by Cult of Mac. Unlike several of its competitors, Apple Music will preserve default recommendation placement for AI-labeled tracks and will not strip creators of royalties.

That hands-off posture stands in stark contrast to the punitive and restrictive steps adopted by rival streaming services. As detailed by Thurrott, Deezer launched an automated AI music detector earlier this year that it claims is nearly ninety-nine percent accurate, with the service reporting that nearly half of daily uploads are AI-generated. Tidal identifies and labels AI tracks while completely blocking them from earning royalties. Meanwhile, Spotify plans to introduce an AI Persona badge for profiles representing artificial identities, withholding those tracks from default editorial and algorithmic recommendations unless a listener explicitly follows the artist.

Working artists draw a sharp line between using generative platforms as personal creative tools and having their specific vocal identities and compositions misappropriated. Nepali singer Sugam Pokharel uses tools like Suno to sketch out arrangement ideas from his own lyrics and compositions before handing them to human producers, a workflow that reduces hours of manual labor. Yet Pokharel and label owner Bimal Adhikari have confronted dozens of their copyrighted songs being altered, retitled, and traded commercially on video platforms without platform-level warnings. Adhikari, who runs Bhavna Music Solution, noted that automated systems could eventually risk flagging original artists for infringement on their own material while anonymous channels disappear and re-emerge under new identities.

Legal and scientific frameworks struggle to keep pace with these operational realities. Nepal's Copyright Act dates back to 2002, long before voice-cloning technology existed, leaving creators to issue public warnings on social media and file individual takedown requests. Suresh Manandhar, an artificial intelligence scientist, points out that while AI lowers the barrier to entry, voice cloning remains the clearest case for mandatory attribution, whereas reworking lyrics or melodies has long historical precedents in South Asian film music. Trade groups including the Recording Industry Association of America and the International Federation of the Phonographic Industry have proposed voluntary frameworks introducing separate Created by AI and AI-Assisted tags, yet no domestic regulatory framework currently exists in Nepal to enforce them.

For now, the operational burden remains squarely on creators who must audit their own distributions and negotiate individual settlements, even as Apple prepares to activate its disclosure tags later this year.

Decoding the Global Divide on Automated Tracks

As major international services diverge on financial penalties and automated detection, the absence of standardized global enforcement leaves creators navigating starkly different operational realities. According to reporting by PCMag, trade bodies including the Recording Industry Association of America and the International Federation of the Phonographic Industry have proposed voluntary frameworks introducing distinct tags such as Created by AI and AI-Assisted. Meanwhile, the Digital Media Association has welcomed these industry-led initiatives for strengthening metadata and listener transparency.

Operational burdens remain heavy for creators auditing their own catalogues, as independent labels and artists await the concrete rollout of Apple Music's disclosure tags later this year. The next step depends on whether platform-level compliance and voluntary trade group standards can bridge the gap between automated distribution and creator protection.