<![CDATA[The increasing integration of generative artificial intelligence into creative and organizational processes challenges traditional assumptions about value creation, authorship, and ownership. In human–AI co-creation contexts, value emerges through iterative interactions between human cognition and algorithmic generation, leading to ambiguity in contribution, attribution, and ownership. Despite growing research on artificial intelligence and digital transformation, existing literature remains fragmented, lacking an integrative framework that explains how value ownership is constructed across multiple levels. This study aims to address this theoretical gap by developing a process-oriented conceptual framework that integrates perspectives from ethics, ownership theory, and co-creation. Using an integrative analytical approach, the study conceptualizes human–AI collaboration as a dynamic system characterized by distributed agency, iterative interaction loops, and multi-level value attribution mechanisms. The proposed model identifies key ethical tensions—authorship ambiguity, value attribution uncertainty, responsibility diffusion, and authenticity erosion—and positions them within an ethical paradox system. The study contributes by reconceptualizing ownership as a multi-dimensional and relational construct while providing a structured framework for analyzing how value is generated, interpreted, and allocated in human–AI systems, offering directions for future empirical research.]]>
