Understanding how organizational AI adoption influences voice behavior: examining the roles of job engagement and LMX

Purpose This study explores how organizational artificial intelligence (AI) adoption influences employee voice behavior through psychological mechanisms. Drawing on conservation of resources theory, we investigate job engagement as a mediator and leader-member exchange (LMX) quality as a moderator in this relationship. Design/methodology/approach We employed a 3-wave time-lagged design with 327 employees from South Korean organizations. Data were collected at six-week intervals: organizational AI adoption and LMX (T1), job engagement (T2) and voice behavior (T3). Moderated mediation analysis tested our hypothesized model. Findings Organizational AI adoption positively relates to voice behavior through enhanced job engagement. This indirect effect is strengthened by high-quality LMX relationships. Employees experiencing high LMX show stronger positive relationships between AI adoption and job engagement, subsequently exhibiting more voice behavior. The moderated mediation index confirms that LMX quality significantly influences how AI adoption affects voice behavior through engagement. Originality/value This study advances understanding of AI'shuman-side implications beyond productivity metrics. By revealing how technological and relational resources interact to influence discretionary behaviors, we contribute to literature on technology adoption, employee engagement and leadership. The findings demonstrate that AI adoption can enhance rather than diminish employee voice when supported by appropriate leadership relationships.