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How the music industry is divided over AI; some labels signed licensing deals for AI that mirror revenue splits they use with YouTube for user-generated content

Financial Times Anna Nicolaou

Context & Ripple Effects

Music-rights owners had already been exploring AI licenses with major music companies, beginning with reported YouTube talks over AI music-generation licensing and later expanding to prospective deals involving several AI developers. The current divide shows that experimentation has moved from a single-platform question to a broader commercial strategy.

The parallel push for tools to detect AI-generated music across the pipeline suggests licensing is being paired with mechanisms to identify what is generated and what rights may attach to it.

First-order effects

  • Labels that sign agreements gain a defined route to monetize AI use of their catalogs, using a revenue-sharing approach familiar from YouTube user-generated content.
  • The split leaves music-rights holders without a uniform negotiating position toward AI companies, even as some establish commercial terms.

Second-order effects

  • AI music providers face a more fragmented rights market: deals with participating labels may broaden legitimate catalog access, while nonparticipants can retain restrictions or seek different terms.
  • Detection and rights-management tools become more operationally important, since revenue sharing depends on distinguishing licensed AI use and generated output across distribution channels.

Third-order effects

  • If these arrangements persist, user-generated-content revenue models could become a template for commercializing generative media rather than relying primarily on takedowns.
  • The industry may separate between licensors that treat AI as a managed distribution channel and rights holders that prioritize tighter control, with bargaining power shaped by each side's catalog and enforcement capabilities.

The trend: Music rights owners are moving toward negotiated AI commercialization, but are doing so through competing models of licensing, attribution, and control.

Discussion

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    The music industry's cautious embrace of AI