Apple Tests AI-Powered Playlist Creator For Apple Music In Latest iOS Beta
This non-deterministic approach could make the tool particularly useful for music discovery, not just routine recommendations
This non-deterministic approach could make the tool particularly useful for music discovery, not just routine recommendations
Apple appears to be moving toward smarter music discovery with a new AI-powered playlist feature hidden inside the first developer beta of iOS 26.4. Codenamed Playlist Playground, the tool is part of Apple’s broader Apple Intelligence initiative and signals a next step in how users curate music in Apple Music.
Found within the beta software, Playlist Playground lets listeners generate custom playlists using natural-language text prompts, moods, or even a selection of up to 10 existing songs. Instead of manually adding individual tracks, users can describe the type of playlist they want, from a vibe or theme to specific emotions and Apple Intelligence will assemble a tailored collection of tracks accordingly.
The feature shares conceptual similarities with older tools like Beats Music’s “The Sentence”, but builds on that idea with more flexibility and generative AI-driven variance, meaning the playlists can differ each time based on the same prompt. This non-deterministic approach could make the tool particularly useful for music discovery, not just routine recommendations.
Right now, Playlist Playground is only active in the iOS 26.4 developer beta and may not show up immediately after updating, as Apple’s backend models download in the background. A broader public beta and eventual official rollout, likely in March or later this spring, are expected, with Apple potentially refining the experience through further testing.
If fully rolled out, the feature could add a new dimension to Apple Music’s playlist ecosystem, which already includes human-curated, algorithmic, and collaborative lists. With text-prompt playlist creation, Apple aims to give users a more intuitive way to shape their listening experiences without piecing together tracks one by one.