While increasing subscription fees due to its market dominance, Spotify is simultaneously leveraging AI-generated music. This strategy could significantly reduce its largest expense—artist royalties—by populating background-listening playlists with royalty-free AI tracks, creating a powerful profit engine.
Related Insights
While generative AI introduces novel complexities, the fundamental conflict over artist compensation is not new. Historical examples, like musicians' families suing record labels over royalties, show these battles predate AI. AI's use of training data without permission has simply become the latest, most complex iteration of this long-standing issue.
As AI tools enable millions of amateur creators to produce professional-quality content, platforms like YouTube and Spotify become less reliant on a small number of mainstream media giants. This diffusion of content creation shifts bargaining power away from traditional studios and labels to the platforms themselves.
The rise of AI music has created a significant challenge for streaming platforms. Fraudsters upload vast quantities of AI-generated music and use bots to generate plays, illegitimately collecting royalties. This industrial-scale "slop" problem threatens the financial integrity of the entire streaming ecosystem.
The fear of AI in music isn't that it will replace human artists, but that it will drown them out. The real danger is AI-generated music flooding streaming playlists, making genuine discovery impossible. The ultimate risk is platforms like Spotify creating their own AI music and feeding it directly into their algorithms, effectively cutting human artists out of the ecosystem entirely.
Despite public industry skepticism, AI music tools are becoming indispensable creative co-pilots for professional songwriters and producers. The CEO of Suno reveals that while many pros use the platform extensively for ideation, they are reluctant to admit it publicly.
To handle royalties for AI-generated music, platforms can analyze the final audio file to algorithmically determine the likely prompt (e.g., "Taylor Swift singing a Gunna song"). This allows for fair royalty splits between the referenced artists, creating a viable monetization path.
STEM FM is challenging the standard music royalty model with a time-based system. An artist's earnings from a subscriber are directly proportional to the percentage of that user's total listening time. This better rewards deep engagement over simple stream counts, aiming for a fairer payout structure for artists.
Historically, the value of content IP like scripts and music declined sharply 30-60 days after release. AI tools can now "reimagine" these dormant libraries quickly and cost-effectively, creating new derivative works. This presents a massive, previously untapped opportunity to unlock new revenue streams from back catalogs.
![Media M&A - [Business Breakdowns, EP.230] thumbnail](https://megaphone.imgix.net/podcasts/8404be2a-a3c6-11f0-9d01-7b00b28a9d50/image/9a48597af1149c3b024e8d2f7327aa89.jpg?ixlib=rails-4.3.1&max-w=3000&max-h=3000&fit=crop&auto=format,compress)
The primary value of AI music generators is the entertainment of creation and style transfer, not passive listening. This positions them as competitors to creative software like GarageBand or games like Fortnite, rather than to streaming platforms like Spotify.
Spotify's early success stemmed from launching in smaller European countries where record labels had less focus. This allowed them to secure more favorable licensing deals and avoid the costly legal battles and poor margins that strangled their US-based competitors, enabling them to reach critical mass first.
