Balancing the Benefits and Challenges of AI: Understanding its Impact on Employee Work Engagement and Burnout

Abstract

This thesis explored how artificial intelligence (AI) impacts work engagement and burnout, using the Job Demands-Resources (JD-R) model to examine AI as both a job resource and demand. Key AI factors included Perceived Adaptability, Quality, Personal Utility, AI use anxiety, and AI-induced job insecurity. The study investigated how personal resources moderate the AI–well-being relationship. Employees with higher personal resources may better leverage AI for performance, while those with lower resources may experience AI as a greater demand. Multi-wave cross-sectional data were collected from employees across industries utilizing AI. Measures included the Utrecht Work Engagement Scale, Shirom-Melamed Burnout Measure, and scales for personal resources. Data analysis involved multiple regression and moderation tests, with post hoc probing for significant effects. Results revealed that perceived quality and utility of AI positively predicted work engagement, while AI use anxiety significantly predicted burnout. Findings offered insights into AI's dual role in shaping employee health.