Against the backdrop of rapid advances in artificial intelligence(AI) and its deep embedding in social structures, global AI governance is taking shape as a new landscape characterized by multi–actor participation and cross–level collaboration. Focusing on four key categories of governance actors—states, international organizations, technology companies, and the public—this paper traces the evolution of their roles and the mechanisms of their interaction in AI governance. By systematically summarizing three main types of relationships—interaction through institutional rules, resource collaboration, and public sphere—it constructs a “rules–capabilities–cognition” closed loop, revealing the pathways of coordination and structural features through which diverse actors engage in standard–setting, capacity building, and societal feedback. In the process of interaction, these actors continuously propel AI governance from unilateral regulation toward negotiated co–governance, gradually forming a multi–actor governance system with networked characteristics and adaptive capacities. This study helps to clarify the relational structures and interaction logics among actors in global AI governance and provides a foundational basis for building more inclusive and effective governance frameworks.

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