With the rapid development of artificial intelligence technology

its cross integration with dance art has given rise to new creative paradigms. This study focuses on exploring the integration path between AI generated dance and traditional choreography theory. By analyzing the complementarity and conflict between the core system of traditional choreography theory (such as Labanation symbol system

motivation development law) and AI technology logic (data-driven algorithm

probability generation model)

a "dynamic complementarity" fusion model is constructed. The research proposes a hybrid creative methodology based on human-computer collaboration

and develops technical paths such as digital translation of traditional action symbols and algorithmic reconstruction of choreography logic. The feasibility of the fusion paradigm is verified through case studies such as ethnic dance variation generation and digital inheritance of intangible cultural heritage dance. Research has found that AI technology can break through the programmatic limitations of traditional choreography

achieve innovative movements

and improve cultural dissemination efficiency. However

it also faces challenges such as controversies over artistic authenticity and algorithmic bias. Research suggests building a collaborative creative ecosystem of "human led AI assisted" and establishing interdisciplinary collaboration mechanisms and ethical norms to provide theoretical support and practical guidance for the deep integration of AI technology and traditional dance art.