How does AI power drive job performance in a human-AI collaboration environment?

In the context of digital transformation, how individual AI capability translates into organizational effectiveness is a core issue in the field of human-AI collaboration. Based on Conservation of Resources (COR) theory, this study utilizes multi-time-point tracking data from 338 supervisor-subordinate dyads. The results show that: First, capability, as a key instrumental resource, has a significant positive effect on job performance; Second, job crafting is the critical behavioral path for converting resources into effectiveness. AI capability enhances performance inducing approach-type job crafting and can inhibit the performance decline caused by avoidance-type job crafting. The study reveals the selection mechanism of human-AI collaboration from resource stock to behavioral, providing theoretical support and managerial implications for enterprises to enhance the effectiveness of digital talent.