Employee–AI Collaboration and Work Well-Being: The Roles of AI-Related Perceived Organizational Support, Workload, and Leader AI Symbolization

Artificial intelligence (AI) is increasingly embedded in organizational work, yet its implications for employee work well-being remain unclear. Integrating Job Demands–Resources (JD–R) theory with organizational support theory, cognitive appraisal theory, and social information processing theory, this study used a two-wave, single-source questionnaire design to examine two pathways linking employee–AI collaboration to work well-being and the moderating role of leader AI symbolization (LAIS). Data from 335 employees in China showed a positive total association between employee–AI collaboration and work well-being. Employee–AI collaboration was positively associated with both AI-related perceived organizational support (AI-related POS) and workload: AI-related POS carried a positive indirect effect, whereas workload carried a negative indirect effect. Because these pathways operated in opposite directions, their summed indirect effect was not statistically significant. LAIS strengthened the AI-related POS pathway and attenuated the workload pathway. Simultaneous path analysis and bootstrap robustness tests yielded the same pattern. These findings characterize employee–AI collaboration as a work arrangement that may be appraised through both resource-gain and demand-related pathways; the two-wave design does not establish causal ordering.