Apple tests text-driven playlist creation tool

Apple has rolled out a new feature in its latest iOS developer beta that allows users to generate customised Apple Music playlists using a simple text prompt, marking a deeper push into artificial intelligence-driven music curation.

Called Playlist Playground within the beta software, the tool enables subscribers to type short descriptions such as “upbeat electronic for a late-night drive” or “soft acoustic tracks for Sunday morning” and receive an automatically generated playlist tailored to that request. The feature builds on Apple’s broader strategy to integrate generative AI across its ecosystem, from messaging to media services.

Apple Music, which counts more than 100 million songs in its catalogue, has long relied on a mix of human editorial curation and algorithmic recommendations. Its flagship playlists, including Today’s Hits and Rap Life, are curated by in-house editors, while personalised mixes such as the Favourites Mix and New Music Mix are powered by listening history and behavioural data. Playlist Playground shifts that balance further towards direct, user-controlled AI creation.

According to developers testing the beta, the system interprets natural language prompts and assembles tracks based on mood, genre, tempo and contextual cues. Users can refine results by adjusting the text prompt or adding follow-up instructions, effectively turning playlist creation into an interactive dialogue. The feature is embedded directly within the Apple Music interface, reducing the need to manually search for individual tracks.

The move comes amid intensifying competition in streaming, where Spotify has introduced AI DJ and AI Playlist features that also allow text-based playlist generation. Spotify’s tools, launched in stages across markets, combine generative AI with user data to create themed playlists on demand. Amazon Music and YouTube Music have similarly expanded personalised recommendation engines, though Apple’s approach appears tightly integrated with its broader device ecosystem.

Industry analysts say generative playlist tools could alter how listeners discover music. Rather than relying on pre-defined genres or editorial categories, users can describe scenarios, emotions or niche themes, allowing AI systems to surface deeper catalogue cuts alongside chart hits. For record labels and independent artists, that shift may open new pathways for exposure, particularly if algorithms surface tracks that would not typically appear in mainstream curated lists.

Apple has been steadily expanding its artificial intelligence capabilities under what it describes as Apple Intelligence, a framework unveiled at its Worldwide Developers Conference. While much attention has focused on AI writing tools, image generation and enhanced Siri functionality, the extension of generative features into Apple Music signals a commercial application aimed at retaining subscribers and differentiating the service.

Apple Music trails Spotify in global paid subscriptions but maintains a strong presence in key markets, particularly among iPhone users. The integration of AI-powered playlist creation within iOS may strengthen that link, as the feature is designed to work seamlessly across iPhone, iPad and CarPlay. Observers note that frictionless integration within the operating system has historically been one of Apple’s competitive advantages.

Questions remain over how transparent the system will be in explaining why specific tracks are selected. Critics of algorithmic curation have long raised concerns about bias, pay-for-placement practices and the opacity of recommendation engines. Apple has emphasised its commitment to privacy, stating that many of its AI processes are performed on-device where possible, though the extent to which playlist generation relies on cloud processing has not been detailed.

Music executives are also watching how generative tools may affect editorial influence. Apple Music has invested heavily in radio-style programming and celebrity-curated playlists, positioning itself as a more artist-friendly alternative to purely algorithm-driven platforms. Whether text-prompt playlists complement or dilute that identity will depend on how prominently the feature is surfaced and how it interacts with human-curated content.

Developers testing the beta report that generated playlists can be saved, shared and further edited, allowing users to add or remove tracks after creation. Early feedback suggests the system performs best with descriptive, scenario-based prompts rather than single-word commands, reflecting broader trends in generative AI where richer input produces more nuanced output.

Regulators in several jurisdictions are examining the broader implications of AI-driven recommendation systems, particularly in relation to competition and consumer transparency. Although playlist generation appears benign compared with other AI applications, the technology sits within a wider debate over how digital platforms shape cultural consumption.

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