AI Resilience Report forChoreographers

Right now, AI is showing up in choreography mostly as a creative partner rather than a replacement. The biggest current example is Wayne McGregor's AISOMA tool, where a custom AI was trained on nearly four million poses from more than two decades of his dance archive ^[1] so dancers can perform a short sequence and the model extends it with new choreographic phrases. Dance Magazine reports that contemporary choreographers like Rashaun Mitchell and Silas Riener are even making works that imagine the implications of AI, using machine learning such as speech-to-text transcription as part of their pieces ^[2].

Tools are appearing for other tasks too: a UK legal analysis notes that American Ballet Theatre has begun exploring AI for talent assessment by analyzing video submissions of dancers to evaluate technique and stage presence ^[3], and that the Bavarian State Ballet experimented with AI-generated set designs for The Nutcracker. But when CalMatters tested today's top video models against real dancers, they concluded that most dancers settled into the view that AI is incapable of capturing the uniquely human aspects of dancing, including improvisation and the energy imparted by audiences ^[4].

Adoption is likely to stay slow for the embodied parts of the job. A new Gallup analysis using a federal exposure index found that choreographers fall around 0.27 to 0.28, while dancers score just 0.04, because the core of the work involves live presence, interpretation and physical skill that generative systems cannot easily substitute ^[5]. The same study found little evidence so far that generative AI has broadly reduced artists' earnings, with hours worked actually rising from 2022 through 2024 ^[5].

Legal friction is another brake: copyright law typically requires human authorship, and AI-generated choreography raises unresolved questions about derivative works, performance rights and licensing ^[3]. On the cultural side, artists like Jonzi D argue that AI should augment human creativity rather than replace it, and that AI-generated art currently exhibits a uniformity that risks creative stagnation ^[3]. So the takeaway for a young person eyeing this career is hopeful: expect to use AI as a brainstorming and prototyping sidekick, but the parts of the job that depend on teaching, rehearsing, and shaping live human bodies in a room together remain very much yours.