From Choreographic Tools to Production Infrastructure: The Paradigm Shift in Dance Creation with Generative AI

Abstract

With the introduction of generative artificial intelligence (AI) into the field of dance, motion capture, model generation, human editing, and platform-based distribution are increasingly interconnected, giving rise to a new cultural production chain. Understanding this transformation merely in terms of AI as a “choreographic tool” fails to account for the ways in which data, algorithms, and platforms continuously reshape the conditions of creative production. Drawing on research on AI-generated dance, theories of the digital cultural industries, and the authors’ own experience with motion-capture practice, this study examines generative AI dance creation across three dimensions: motion data, generative editing, and platform distribution. It argues that generative AI is expanding from a localized creative tool into a broader form of production infrastructure, without thereby acquiring the status of an autonomous creative agent. The resulting tensions are manifested in the computability and irreducibility of embodied experience, the lowering of participation barriers alongside the concentration of foundational resources, and the proliferation of content alongside the weakening of cultural context. Based on these findings, the study proposes several pathways, including contextualized data development, embodied participation, accountability and traceability, and tiered evaluation, to foster an industrial practice of generative AI-assisted dance creation that combines cultural depth with public value.