Enhancing Employee Innovation Through Dependence on AI: The Mediating Role of Cognitive Flexibility and Moderating Effect of Job Complexity

Drawing upon the Job Demands-Resources (JD-R) model, this study explores the mechanism through which Dependence on AI affects employees’ innovative behavior, focusing on the mediating role of cognitive flexibility and the moderating role of job complexity. Using questionnaire data from full-time employees collected between December 2024 and February 2025, this study conducts confirmatory factor analysis, correlation analysis, hierarchical regression and the Bootstrap test with AMOS, SPSS and the PROCESS macro. The results show that Dependence on AI significantly and positively predicts employees’ innovative behavior, and cognitive flexibility plays a partial mediating role between the two variables. Job Complexity serves as a negative moderator for the association between Cognitive Flexibility and Innovative Behaviors, and the positive linkage of Cognitive Flexibility to Innovative Behaviors becomes relatively weaker when Job Complexity is high. This study expands the cognitive mediating path through which Dependence on AI influences innovative behavior, refines the theoretical boundary of demand–resource interaction in the JD-R model, and provides practical implications for organizations to rationally guide human–machine collaboration and enhance employees’ innovative ability in intelligent scenarios.