Spotify is expanding its integration with third-party AI assistants as it seeks to make music, podcasts, and audiobooks accessible through conversational requests. The company outlined its strategy alongside third-quarter 2026 earnings, reporting 788 million monthly active users and €4.97 billion in revenue, an increase of 11% and 16% year over year, respectively.
According to its October 22 earnings report, Spotify also reached 306 million premium subscribers, representing 9% annual growth. Operating income rose 15% to €672 million, while its gross margin improved to 33%.
Spotify Expands Integrations With AI Assistants
Co-CEO Gustav Söderström said Spotify expects AI agents to change how listeners discover and access entertainment. Rather than requiring users to search for artists or manually create playlists, AI assistants could handle those tasks through natural-language conversations.
Spotify has already integrated its services with Meta Muse, ChatGPT, and Claude, allowing users to request songs, podcasts, audiobooks, and personalized playlists through external AI platforms. In September, the company became the first music streaming service to integrate with Meta’s Muse assistant.
Through Muse, users can ask Spotify to create playlists for upcoming activities, save songs, resume podcasts, or schedule music playback. The integration also supports personalized audio briefings based on information users provide to their AI assistants.
Söderström said Spotify aims to make its content accessible through any AI agent rather than requiring listeners to interact exclusively with its own application. He also reported encouraging adoption of Spotify’s services through existing agent integrations, although the company did not disclose specific usage figures.
AI Personalization Uses Spotify Listening History
Spotify is also developing conversational features within its own platform to provide more detailed music recommendations. Söderström described the service as an intelligent media platform capable of understanding requests involving listening history, musical characteristics, and individual preferences.
For example, users could ask Spotify to identify favorite songs from years of listening activity, adjust their playback speed, and organize tracks according to musical key and beats per minute. The system could then combine those songs into a running playlist tailored to the listener’s preferred pace.
Spotify’s recommendation systems draw on listening activity dating back to 2008, including frequently played artists, skipped tracks, and music discovery patterns. Söderström emphasized that this information remains within Spotify’s systems rather than being transferred directly to external AI providers.
When a user requests music through another AI assistant, Spotify processes the request using its own data and recommendation technology. This arrangement allows external agents to interact with the service without independently accessing Spotify’s underlying listening records.
Spotify Sees AI Agents as an Opportunity for Growth
Söderström argued that entertainment differs from routine activities that AI agents are designed to automate. While users may want assistants to handle administrative work, they still want to experience music and other entertainment themselves.
Spotify’s approach contrasts with restrictions adopted by some technology companies, including Amazon’s decision to block Meta Muse from accessing its shopping platform. Spotify instead views AI assistants as additional channels for connecting users with its streaming services.
The company is also developing its own AI-powered discovery tools, including personalized DJ experiences and prompt-based playlists. These features form part of Spotify’s efforts to increase engagement while expanding access through external AI platforms.
Featured image credits: Wikimedia Commons
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