Abstract: As artificial intelligence is increasingly embedded in public service systems, how human–machine interaction shifts from fragmented technological practices to a stable administrative action structure remains under-theorized. Drawing on an action-structure perspective, this study analyzes the formation and operation of human–machine interaction across three dimensions: element construction, embedding pathways, and risk regulation. The analysis shows that human–machine interaction is integrated into a composite “human–machine–human” action network through the reconfiguration of bureaucratic and citizen roles and the sustained coupling of technical systems and organizational arrangements. This embedding unfolds along three pathways—instrumental rationality, value orientation, and innovative development—through efficiency optimization, procedural standardization, and institutional restructuring. While producing differentiated embedding effects, these pathways also generate structural risks, including operational dependence, responsibility ambiguity, and coordination imbalance, giving rise to tensions between technological empowerment and governance constraints. The study argues that effective embedding depends on anticipatory institutional design and dynamic risk adjustment mechanisms. This research advances the understanding of how administrative action structures evolve under AI intervention and how related governance risks emerge.