Ping Liu, Ling Yuan, Zhihong Tan
ABSTRACT As artificial intelligence (AI) becomes increasingly embedded in organizational operations, how employees perceive and respond to AI has become a critical issue in human resource management. Drawing on the Job Demands–Resources (JD‐R) model, this study conceptualizes employees' challenge and hindrance appraisals of AI (AI awareness) as cognitive job demands and develops a “dual appraisal–dual pathway–dual outcome” framework. Specifically, challenge appraisals (CA) and hindrance appraisals (HA) are proposed to influence innovative behavior and knowledge hiding through psychological empowerment and emotional exhaustion, respectively, with leadership developmental feedback (LDF) serving as a boundary condition. Using three‐wave matched data from full‐time employees across multiple industries ( N = 346), the results show that: (1) CA significantly increases innovation and decreases knowledge hiding through psychological empowerment; (2) HA increases knowledge hiding and decreases innovation through emotional exhaustion; and (3) LDF strengthens the positive effect of CA on empowerment. The study translates AI from an exogenous technological attribute into a cognitive job demand within the JD‐R framework, integrates proactive and defensive outcomes within a unified mechanism, and identifies the orientation‐sensitive boundaries of job resources. It further offers organizations a practical pathway—appraisal identification, empowerment enhancement, and differentiated feedback—to foster innovation and reduce knowledge hiding during digital transformation.