Subordinates’ human–AI collaboration and leaders’ diverse responses: A dual-process perspective

Abstract: Human–AI collaboration has emerged as a key driver of organizational innovation and efficiency, with leaders playing a pivotal role in this process. However, extant research has primarily focused on the employee perspective, largely overlooking leaders’ diverse cognitive and behavioral responses to their subordinates’ human–AI collaboration. Consequently, it remains difficult to explain why leaders’ subjective judgments of human–AI collaboration may diverge from its actual performance outcomes. Such perceptual biases may not only influence how leaders evaluate and manage human–AI collaboration but also underscore the limited understanding of the mechanisms underlying leaders’ diverse responses and their effectiveness. To address these gaps, this project draws on dual-process theory and comprises three interrelated studies. Study 1 examines leaders’ “cold” response mode by investigating how their attributions regarding subordinates’ motives for engaging in human–AI collaboration and their perceptions of its future implications elicit development- and change-oriented behaviors. Study 2 examines leaders’ “hot” response mode by revealing how subordinates’ human–AI collaboration evokes leaders’ feelings of relative deprivation and prompts them to engage in retaliatory incivility as a defensive stress response. Study 3 adopts a dynamic perspective to compare the effects of leaders’ different behavioral responses on the sustainability of human–AI collaboration, thereby enhancing the effectiveness of human–AI collaboration and facilitating organizations’ digital and intelligent transformation.