AI and the Future of Niche Music Listening: An Interface For Every Fan

What if AI agents could transform music streaming by uniting platforms into a single personalized experience? Discover how this innovation could boost niche music listening and redefine discovery.

AI and the Future of Niche Music Listening 

By Con Raso, Managing Director of Tuned Global

In our current app-based world, niche streaming services that primarily serve one market, ethnic communities, or genres are fighting a hard fight against established global or larger regional players. Yet we may be at a crucial moment when market dominance may be seriously challenged by the little guy. The catalyst: AI agents and their impact on music access and engagement, including, but not limited to, search and discovery.

AI agents are designed to scan the environment, make decisions, and take action to achieve specific goals. No one knows exactly how these agents will shape music listening and discovery, but we have hints including general search tools like Google’s AI snippets and Arc Search’s “Browse for Me,” which use LLMs to summarize web pages’ text. Could a similar approach lead to a universal interface for music, one that relies on AI agents, be on the not-too-distant horizon? If so, what will it mean for DSPs and the music industry, writ large?

In today’s music streaming landscape, giants like Spotify and Apple Music dominate. While they boast extensive libraries of music, including global hits popular around the planet, discovery and user experience remain significant issues. Big DSPs have to find the common denominator when it comes to user experience and interfaces. They use AI to surface potentially intriguing content for listeners, but they have a habit of leaving niche offerings buried beneath an overwhelming pile of sounds. Data supports this: 152 million songs on streaming platforms had less than 1,000 streams in 2023, while 45 million songs had zero streams. Moreover, music’s smaller communities and emerging artists are struggling more and more to reach audiences through a thick layer of hits, or so analysis suggests.

“a surge in niche streaming services tailored to specialized interests and communities”

At the same time, the world has witnessed a surge in niche streaming services tailored to specialized interests and communities. Small Pacific Island nations and local telecom providers from Greenland to Ethiopia are creating streaming music services tailored to the cultural needs, values, and interests of their customers. These providers don’t need comprehensive catalogs with every single international hit, but can license selectively, keeping costs relatively low. Still, they face a significant challenge: Amidst this diversity, users may not be able to navigate and discover their content amongst a myriad of platforms.

This is where AI agents might change things. Picture a single, malleable interface capable of gathering specific tracks or data from all these musical niches, offering users a seamless and personalized experience unlike any other. 

“all audiences are not alike”

Currently, when we are building a streaming service, we design an interface that connects to a static music library and provides a series of compromises to engage all audiences somewhat. But all audiences are not alike: Consider how the user experience needs to be markedly different if you’re listening to classical music or rock, and how your needs may vary depending on whether you are 14 or 40 years old, whether you’re running or playing a video game. 

Personal preferences can come into play, too. Some people love a simple interface that lets them hit play and forget about it. Others want to dive deeply into information about the artist, songwriter, producer, and featured musicians on the tracks they love. What if a single, stable interface did not exist, and, thanks to AI, the interface designed itself for you? This is what AI agents could do. You would be presented in a single interface with music from various platforms and can play this music with a single click. 

The music they could access may be limited to either freemium services or services that you subscribe to, giving agents access to your history, tastes, and comments.  AI could then generate personalized playlists that transcend mere algorithmic suggestions, offering users a curated journey through their musical interests and fundamentally reshaping the music streaming experience. It might even weave these recorded, static tracks together with generated musical interludes or commentary, something already being explored by some DSPs and platforms.

“an AI-powered interface pulling together music from across the internet”

Although still in its conceptual stage and very much in flux, an AI-powered interface pulling together music from across the internet could happen. The implications for the music business as it exists are many. Companies could thrive that provide niche experiences, whether that is the music itself or the analysis of that music for users, as long as their systems are open to AI agents.

This feels futuristic, but it may be approaching more swiftly than you think, as AI hardware and model engineering leap ahead. A whole new type of AI that does very specific things on a specific, non-cloud-connected device is emerging, and it will have implications for our music experiences. Just as we moved from CDs, to mp3s and flip phones, to smart app-based devices, the next generation of devices or services and their interaction with music and music data will be new and different.

As this new reality emerges, there will be winners and losers among both large and more niche players, of course, but the key mandate will be to experiment with these technologies and find how existing app-based services can remain relevant in a new landscape.

This opportunity to experiment will be open to all, big or small—and the ultimate winners will be music fans.