Human agency in AI-driven work transformation: exploring hospitality employees’ adaptation strategies

This study investigates how human-machine interaction affects employees’ cognitive and behavioral processes in adaptation, and how these in turn influence efficiency which is a topic less explored by prior research focused on technology acceptance and customer experience. This study collected data through structured interviews with employees in smart hospitality and employed coding methods based on grounded theory. Research findings suggest that (1) Employees’ perceptions include social perception (perceptual mind and reliability) and functional perception (ease of use and usefulness), both of which reduce technology anxiety; (2) Technology anxiety triggers learning motivation by creating a sense of ability crisis (task adaptation difficulties, job insecurity, and skill uncertainty), leading to self-directed learning and training participation; (3) Learning behaviors enhance human resource efficiency (manifested as improved work efficiency, stronger human-machine collaboration, and higher service quality). This study contributes by addressing a research gap in employee adaptability and human resource efficiency during hospitality's intelligent transformation.