This study examines data governance issues arising from the expanding use of data and artificial intelligence (AI) in the performing arts through a stage-based data pipeline framework. The pipeline consists of six stages: collection, cleaning and processing, storage and management, AI training, generation and utilization, and reuse and sharing. Using seven domestic and international cases, the study applies pattern-matching analysis to identify dominant governance factors at each stage, focusing on six dimensions: legitimacy, quality, control, transparency, accountability, and usability. The findings show that governance issues emerge structurally along the data pipeline rather than from specific technologies. Legitimacy was dominant in AI-based creative systems, quality in real-time performance environments, control in digital archives, and usability in platform-based sharing systems. The study highlights the need to establish stage-specific governance frameworks suited to AI-driven performing arts environments.

This study examines artificial intelligence (AI) discourse in Korean dance studies between 2017 and 2025 from the perspective of human–technological–bodily relational networks and investigates how AI is transforming the discursive structure of the field. To achieve this, phenomenological embodiment theory, posthumanist theory, and technology-mediated art discourse were employed as analytical frameworks, and a qualitative literature review was conducted on thirty-five academic articles published in Korean scholarly journals. The findings indicate that AI functions as an agent mediating bodily experience, creative processes, and modes of reception across the domains of education, creation, and audience engagement. As a result, the body is being reconstituted as a relationally-constituted entity, creation as a collaborative process, and reception as a participatory experience. Overall, AI discourse in Korean dance studies extends beyond discussions of technological application toward an exploration of how meaning is generated through human–technological–bodily relations, representing a discursive shift that calls for a re-examination of the concepts and boundaries of dance studies.

The purpose of this study is to explore the ethical situations that field workers can face in dance art work with AI, especially focusing on the 'body alienation' situation of dancers. The study focused on literature research on AI and body alienation, semi-structured one-on-one phone interviews involving engineers and dancers who have experienced related work in the actual field, and structured one-on-one written interviews involving choreographers. As a result, we discovered situations and types of body alienation that can occur, such as ‘human body instrumentalized for AI learning’, ‘body alienation due to differences in performance capabilities between humans and AI’, and ‘body alienation due to capital and power’. The body alienation that can occur at this time includes not only issues of portrait rights, intellectual property rights, and copyright, but also personal privacy, labor alienation, psychological alienation, and biological alienation. It is expected that this study will be used in various ways as a basic study examining ethical factors that should be considered in the workplace of dance art using AI.