Why AI Could Make Human Jazz Popular Again

As a musician and music-lover, the artificial intelligence revolution terrifies me in many ways. AI apps such as Suno have already shown extraordinary potential to generate catchy and professionally-produced music in certain genres. So it isn’t hard to imagine a world in which, for example, session musicians, jingle writers and purveyors of educational music for kids could soon lose their livelihoods to machines.

At the same time, I’m fairly optimistic that jazz — one of the most commercially underappreciated of all the musical styles, and the one closest to my heart — will survive and thrive in the new AI ecosystem. A 2024 year-end music report by Luminate ranked jazz 10th out of 11 “selected top genres” in the US, where it was nestled between classical and children’s music and commands less than 1% of total on-demand streams.

AI might be the key to improving on those abysmal numbers by highlighting what I call the “jazz model”: a way of making music that puts live, verifiably human performance at the center. And that model may point to a path of survival for other human artists looking to carve out a niche in our AI future.

To see why, it helps to look at what generative AI actually does well — and what it struggles with. It can mine vast troves of patternistic text, images, audio and video, then turn it into something you might want to consume. That works quite well, for instance, for pop and rock music, in which songs tend to clock in at around 3-4 minutes and follow the predictable pattern “verse-chorus-verse-chorus-bridge-chorus-end.”