Different types of human–AI interaction and employees’ knowledge territorial behavior: the role of organizational dehumanization and paradoxical leadership

Introduction: As artificial intelligence (AI) becomes increasingly embedded in organizational workflows, understanding how human-AI interactions shape employees' knowledge territorial behavior has become a critical issue in digital transformation. Drawing on conservation of resources theory, this study examines the differential effects of enhanced and impeded human-AI interaction on employees' knowledge territorial behavior, with organizational dehumanization as the underlying psychological mechanism and paradoxical leadership as a boundary condition. Methods: We tested the hypotheses across two studies. Study 1 used a scenario-based experiment to establish the causal effects of different forms of human-AI interaction. Study 2 employed a two-wave field survey to validate the full moderated mediation model in a real-world organizational context. Results: Enhanced human-AI interaction was negatively associated with knowledge territorial behavior, whereas impeded human-AI interaction was positively associated with such behavior. Organizational dehumanization significantly mediated these relationships. In addition, paradoxical leadership moderated these effects: higher levels of paradoxical leadership strengthened the negative effect of enhanced human-AI interaction on organizational dehumanization and attenuated the positive effect of impeded human-AI interaction on organizational dehumanization. Discussion: These findings reveal the double-edged effects of human-AI interaction on employees' knowledge territorial behavior. This research extends the literature on the antecedents of knowledge territoriality, highlights organizational dehumanization as a key psychological mechanism, and identifies paradoxical leadership as an effective managerial approach for facilitating human-AI collaboration in modern organizations.