Beyond the Playlist: How AI Is Reshaping Music for Fitness

Music isn’t background. It’s infrastructure. And AI is what finally lets us treat it that way. 

For decades, music in fitness has been treated as decoration — a backdrop to the real work being done.

That perspective doesn’t quite hold when you look closer.

In practice, music has always been doing far more than most operators have given it credit for.

“Think about what music is doing in a class,” says Rusty Greene, founder of FitRadio. “It’s setting the tempo people move to, cueing the transitions, controlling how hard the room pushes and shaping whether a member walks out saying ‘that was amazing’ or ‘that was fine.’ That’s not decoration — that’s load-bearing.” 

That distinction reframes music entirely, moving it out of the realm of ambiance and into something structural, deliberate and ultimately measurable.

That’s the lens FitRadio has built around.

Music as Infrastructure

When Greene describes music as infrastructure, he’s pointing to a layer of the fitness experience that has always been there, but hasn’t been given the right level of priority. 

“When we call it infrastructure, we mean it sits underneath the product experience the same way lighting, equipment or programming does,” he says. 

In many facilities, that layer remains inconsistent — shaped by individual instructors, pieced together through consumer streaming platforms or left to chance depending on who is teaching and when. 

The impact of that inconsistency is often felt, even if it’s not always explicitly identified. Members experience it as a class that feels flat or disconnected. Operators see it in uneven class ratings and missed opportunities to fully define the brand experience.

Part of the challenge is that most music technology wasn’t designed for fitness in the first place.

“Streaming platforms have built extraordinarily sophisticated recommendation engines, but they are designed around personal taste and listening behavior,” says Greene.

In a training environment, music isn’t about preference, it’s about function. It needs to match intensity, guide pacing, support transitions and align with the structure of a workout. A track that works perfectly in one moment can fall flat in another.

“Spotify doesn’t know whether you’re lifting, running or cooking dinner,” Greene explains. “In contrast, FitRadio was built around the premise that the music has a job to do.” 

That level of specificity requires a different kind of intelligence — one that understands not just what a song sounds like, but how it performs.

How FitRadio Is Applying AI

That’s where FitRadio has focused its efforts, building an AI engine designed specifically for training environments.

“There are two layers to it,” Greene explains. “First, we use AI to analyze music across dimensions that matter for training, such as BPM, energy curves, vocal intensity, build and drop structure, harmonic density. Then it’s mapped to specific training modalities.” 

Those distinctions are important. As Greene puts it, “HIIT music isn’t strength music isn’t yoga music, and the distinctions get granular.” 

The second layer is how that intelligence is applied.

“We use AI to pair and sequence that music to workouts in real time, so a cycling class and a Pilates class pull from the same catalog but get fundamentally different experiences.” 

That difference becomes clear when compared to general-purpose music platforms. 

“They’re optimizing for listening time and personal taste,” Greene says. “We’re optimizing for physical performance.” 

The distinction ultimately plays out in how the system behaves — matching energy curves to intervals, structuring transitions and aligning music to movement in a way that supports output, not just enjoyment.

What AI Actually Unlocks

In a market saturated with AI claims, Greene is direct about what matters in practice. He says it’s two things: “Scale and precision.”

A skilled human curator can build a high-quality class playlist, but doing so takes time, and more importantly, it doesn’t scale.

“AI can analyze hundreds of thousands of tracks against the energy profile of a specific workout type and assemble class-ready mixes in seconds,” Greene explains. 

That capability extends beyond speed. It allows the same underlying catalog to be dynamically shaped for different class formats, instructor styles, times of day and member demographics — all simultaneously, without sacrificing quality or intent.

Consistency becomes the other major advantage, particularly for operators managing multiple locations.

“A multi-location operator wants every studio to feel on-brand,” Greene says. “Human curation drifts. AI doesn’t.” 

The result is a more standardized experience across locations, without requiring instructors to spend hours building playlists on their own time — a shift that not only improves consistency, but also removes a meaningful operational burden.

The Overlooked Risk: Licensing

While experience and efficiency tend to dominate the conversation, there is another dimension that often goes unaddressed — licensing, which Greene says is a bigger issue than most operators realize and the gap is widening. 

“Consumer services like Spotify and Apple Music aren’t licensed for commercial use and a gym playing them in class is exposed,” he says. “On top of that, you have four performance rights organizations (ASCAP, BMI, SESAC, GMR), each with their own rate structures and most operators are either underpaying, overpaying or unknowingly out of compliance.”

FitRadio solves this by handling the whole stack. 

“We hold the commercial licenses with the major labels and we help operators navigate the PRO side, which gets complicated because public performance rates are tied to facility size and capacity, so a one-size-fits-all approach doesn’t actually work.”

For a franchise system with a hundred locations, that’s the difference between “we have a music strategy” and “we have a legal liability.”

From Background to Business Lever

For operators, the impact of getting music right extends well beyond the playlist itself. It shapes the thing members are actually buying — the experience of the class.

 “When a workout feels great, people come back. When it feels flat, they don’t, and they can’t always articulate why. A lot of the time, the ‘why’ is the music,” says Greene.

The impact is measurable, from class ratings and instructor performance to retention over time. Instructors who consistently deliver strong music tend to build larger followings, fill more classes and stay longer. For operators, that translates into a more stable and more predictable business.

And yet, despite its influence, music is still often treated as a one-time decision rather than an ongoing lever.

“Most operators pick a music solution once, set it and forget it,” Greene says. “They don’t revisit whether it’s actually working for their class formats or their brand.” 

That approach leaves performance on the table. Music is one of the few variables in a fitness business that can be adjusted quickly and felt immediately, within a single class, across a single day.

Treating it as a lever, rather than a checkbox, is where the advantage begins.