Artificial intelligence knowledge hiding: job characteristics and mastery climate

Purpose Drawing on the job design model and adaptive cost theory, this study investigates the impact of artificial intelligence (AI)-enabled task and knowledge characteristics on knowledge hiding. It also explores the moderating role of mastery climate. Design/methodology/approach This study collected data from 357 employees in high-tech firms using a two-phase survey to empirically test the proposed hypotheses. Findings The results indicate that AI-enabled task characteristics (skill and task variety) and knowledge characteristics (specialization, problem solving and job complexity) drive employees to hide knowledge from colleagues. Furthermore, a mastery climate effectively mitigates the impact of AI-enabled task and knowledge characteristics on knowledge hiding. Originality/value This study advances understanding of the relationship between AI and knowledge hiding by shifting attention from employees’ psychological reactions to the structural transformation of work, showing how AI-enabled job design reshapes tasks and generates adaptive costs that foster knowledge hiding.