AI music creators: music’s superfans

Not a week seems to go by without some big news in the world of music AI. Hot on the heels of UMG’s Udio deal, GEMA just secured a favourable ruling against open AI (via Reuters). Over the course of the year, however, court rulings have fallen roughly evenly for media companies and AI companies, or have had such narrow interpretations applied that they have limited use as effective legal precedents. It is becoming clear that legislation, litigation, and regulation cannot move quickly enough for media companies to keep up with AI. But even if this wasn’t the case, there is a new dynamic that the music industry needs to get its head around: consumers that use gen AI to make music are also some of the industry’s most valuable superfans.

In so many respects, AI is best considered as an accelerant rather than something entirely new, intensifying pre-existing trends. AI music absolutely fits this trend. Over the course of the last decade – including a super-charged COVID bump – accessible music tech has enabled ever-more people to become music creators. AI simply lowered the barriers to entry even further. The debate over whether a text prompt constitutes creativity will continue to run (just like the same debate still runs for sampling), but what is clear is that more people are now making music because of AI. Thom Yorke might have sung ‘Anyone Can Play Guitar’ but truly anyone can write a text prompt. Why this matters: it enables more music fans to take one step further and actually make music – the definitive expression of fandom.

Playing and creating music has long been the ultimate superfan behaviour. Whether that be a teen learning to play the riff for ‘Smells Like Teen Spirit’ in the ‘90s or a kid making music in her bedroom with BandLab today. It should come as little surprise that gen AI music users also tend to be music superfans. According to data from the forthcoming MIDiA report AI and consumer creation: The superfan factor, gen AI music users over-index for every music fan metric. And by a lot. This includes being four times more likely than overall consumers to buy merch and one and a half times more likely to have a music subscription. They also strongly over-index for all streaming consumption metrics.

Of course, arguably the biggest gen AI music risk is bad actors creating AI slop at scale, whether that simply be to harvest lean-back listening royalties or to wash dirty money. However, the music industry must not paint all gen AI music creators with the same brush. We can debate the quality of the music until everyone is red in the face, and undoubtedly there needs to be new lanes carved out for this music to occupy. What cannot be ignored is that consumer-creators of AI music are also many of the music superfans that are disproportionately delivering monetary value into the music industry ecosystem. In some respects, this risks being a rerun of music filesharing: the biggest fans are doing something the music industry doesn’t want them to. This time though, the stakes are higher as they are also generating a major portion of its revenue.