Hongyi Cai, GE Yu-hui, Heng Zhao
As technological revolutions continue to advance, AI increasingly emerges as a focal driver for enhancing innovation quality. Grounded in coping theory, this study develops a moderated dual-pathway model to examine the mechanisms through which AI-related task complexity influences innovative work behavior. A three-wave field survey was conducted among 353 employees from high-tech enterprises in Beijing and Shanghai. Hypotheses are tested via structural equation modeling. The findings reveal that AI-related task complexity significantly promotes innovative work behavior by fostering problem-focused coping while simultaneously suppressing it by triggering emotion-focused coping. Moreover, AI opportunity perception is found to moderate these relationships, strengthening the positive effect of problem-focused coping and attenuating the negative effect of emotion-focused coping on innovation. This study advances theoretical understanding of employee behavioral responses in AI-integrated work contexts and offers practical insights into how organizations can leverage AI to stimulate innovation among their workforce.