From Job Insecurity to Burnout in the Age of Artificial Intelligence: The Mediating Role of Work Engagement and the Moderating Role of Artificial Intelligence Self-Efficacy

The study investigates the impact of job insecurity on employee burnout by emphasizing the mediating role of job involvement and the moderating role of self-efficacy in the use of artificial intelligence. Based on the Job Demand-Resource model and the Conservation of Resources theory, this study has explored how both psychological and technological resources shape employees’ responses to the workplace. Through a structured survey, data were collected from 430 employees of Pakistan’s software and IT firms and analyzed using structural equation modeling (SEM-PLS). Results indicated that job insecurity significantly increases burnout while simultaneously reducing job involvement. Moreover, job involvement has negatively influenced burnout, confirming its mediating role between insecurity and burnout. Besides, employees with higher AI self-efficacy reported stronger engagement, as self-efficacy was negatively associated with job insecurity and job involvement. These findings highlight the complex interplay among stressors, engagement, and technological confidence in shaping employee well-being. In addition, the current study contributes to theory by integrating AI-related self-efficacy into established stress-strain frameworks and by offering practical implications for organizations to minimize burnout by increasing employee involvement, reducing insecurity, and strengthening digital competencies.