Artificial Intelligence, Transformational Leadership, and Job Performance: Mediating Role of Job Engagement and Moderating Role of Work Passion

Abstract

This study investigates the relationships among Artificial Intelligence (AI), perceived usefulness of AI, transformational leadership, job engagement, and job performance, with the moderating role of work passion. Drawing on the Job Demands–Resources (JD–R) model and the Technology Acceptance Model (TAM), the study proposes a research model explaining how technological and leadership resources jointly influence employee performance in the context of digital transformation. A quantitative approach was employed, with data collected through an online survey of 345 employees at five leading joint-stock commercial banks in Vietnam. Partial Least Squares Structural Equation Modeling (PLS-SEM) was applied to test the proposed hypotheses. The findings reveal that perceived usefulness of AI is the strongest indirect predictor of job performance through the mediating role of job engagement. The results also confirm that transformational leadership significantly enhances employee engagement, particularly through inspirational motivation and individualized consideration. Artificial Intelligence, as an organizational resource, further strengthens engagement by reducing workload and supporting decision-making processes. Furthermore, work passion plays a moderating role in the relationship between job engagement and job performance, with harmonious passion amplifying this relationship while obsessive passion may reduce its marginal effect. These findings highlight the importance of integrating AI applications with effective leadership practices to foster employee engagement and improve job performance in modern digital organizations.