As a musician and music lover, the artificial intelligence (AI) 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 is not 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 am 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 percent of total on-demand streams.
Illustration: Yusha
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. That model might 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 pop and rock music, in which songs tend to clock in at about three to four minutes and follow the predictable pattern “verse-chorus-verse-chorus-bridge-chorus-end.”
However, great jazz has two things that help set it apart. First, it is often harmonically groundbreaking (Miles Davis’ Kind of Blue, which introduced the world to modal jazz; John Coltrane’s Giant Steps, which cycles through mind-boggling key changes). Second, the genre experiments with novel song forms (Ornette Coleman’s Free Jazz: a Collective Improvisation). More than a century after the birth of jazz, my favorite contemporary players — including the guitarists Julian Lage and Kurt Rosenwinkel — continue to push the boundaries of timbre and harmony.
I have tried to test AI’s ability to replicate the depth of the sound and have been disappointed in the output. Suno prompts such as “create an instrumental jazz recording that pushes boundaries of form and harmony; experiment with dissonance and key changes” result in something I might play on my stereo at a polite holiday party with extended family. However, there was not anything novel or boundary-pushing about it, nor did it hit me on an emotional level.
Obviously, it is premature to say that the technology would never be able to create good jazz. Yet even if that happens, it is likely that we would start to distinguish more sharply between craft — polished, repeatable style — and art, which we would reserve for creative work that is visibly, even vulnerably, human.
A recent Pew Research Center report on how US adults viewed AI found that 53 percent of people thought the technology would worsen the ability to think creatively, which suggests many would be looking for ways to believe that creativity still exists.
What genre can do that better than jazz? Imagine piling into clubs such as the Village Vanguard, where people can sit so close as to watch the performers sweat and where each performance is improvised, unique and imperfect. In that moment, they can marvel at the way human lungs produce expressive trumpet solos and the human fingers sliding up and down the upright bass. Virtuosos would be celebrated, much as great athletes are, as living celebrations of what can be accomplished with hard work, even without machines.
I suspect similar dynamics would extend to other art forms as well. AI would excel at making pastiche — knocking out competent genre fiction, portraits and decorative sculpture. However, the work we prize the most would be the avant-garde, the risky and idiosyncratic, and there would be greater demand for methods to authenticate that it was produced by human hands.
Even creators whose art is not traditionally performance-based might have to show their process, perhaps by livestreaming from their studios or sharing unedited drafts, precisely so audiences can experience and reward the distinctively human labor behind the finished piece.
Long before becoming a markets columnist (my day job for this publication), my dream was to become a jazz guitarist. Seeing how hard it was for working players to earn more than a modest middle-class income eventually pushed me toward another career, but I have never stopped cheering for the people who stayed in the music.
It has been nearly a century since jazz dominated popular music and six decades since the massive hit albums of Davis, Coltrane, Dave Brubeck and others. Yet, as scary as AI is for musicians on the whole, I would love to believe that the upheaval will finally bring about a renewed appreciation for the jazz performers that I hold so dear — a group of artists that the world has long taken for granted.
Jonathan Levin is a columnist focused on US markets and economics. Previously, he worked as a Bloomberg journalist in the US, Brazil and Mexico. This column reflects the personal views of the author and does not necessarily reflect the opinion of the editorial board or Bloomberg LP and its owners.
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