Fostering proactivity in the age of AI: exploring the interplay of job reflection and coaching leadership

Purpose This study examines the impact of artificial intelligence (AI) adoption on employee proactive behavior in South Korean organizations. Drawing on social cognitive theory, we investigate the mediating role of job reflection and the moderating effect of coaching leadership in this relationship. Our research aims to address the critical gap in understanding how AI adoption influences employee proactivity, a crucial behavior in dynamic, technology-driven environments. By exploring the cognitive processes and leadership factors involved, we seek to provide insights into how organizations can leverage AI adoption to foster proactive behavior while emphasizing the importance of reflective practices and supportive leadership. Design/methodology/approach We employed a time-lagged survey with 405 employees across three waves. AI adoption, coaching leadership and control variables were measured at Time 1, job reflection at Time 2 and proactive behavior at Time 3. Hierarchical regression and bootstrapping analyses were employed to test hypotheses. Findings Our results reveal that AI adoption positively relates to proactive behavior, with job reflection mediating this relationship. While coaching leadership moderates the relationship between AI adoption and job reflection, the hypothesized moderated mediation effect was not supported, suggesting job reflection’s mediating role remains consistent regardless of leadership level. This finding highlights the robustness of job reflection as a cognitive mechanism in the AI adoption context. Originality/value This study advances understanding of the mechanisms linking AI adoption to proactive behavior by identifying job reflection as a key mediating process. It provides insights into how organizations can leverage cognitive processes to enhance employee proactivity during AI implementation while revealing the complexity of leadership’s role in this relationship.