The Double-Edged Sword of AI for Employee Recovery: Understanding Its Dual Impact Through Competence Satisfaction and Frustration

Abstract

This thesis investigated the "double-edged sword" of artificial intelligence (AI) in the workplace, examining how employees’ cognitive appraisals of AI affected work recovery. Drawing on the Challenge-Hindrance Stressor Framework and Self-Determination Theory, this study explored how appraising AI as an empowering challenge (techno-mastery) or an overwhelming hindrance (techno-complexity) influenced psychological detachment and mastery experiences via the basic psychological need for competence. Data were collected from 341 full- time U.S. employees using AI via a three-wave, time-lagged survey design. Path analysis results revealed an asymmetrical mediation pattern: the pursuit of growth-oriented mastery experiences was exclusively mediated by competence satisfaction, whereas psychological detachment was exclusively mediated by competence frustration. Thus, AI techno-mastery promoted recovery by satisfying competence and reducing frustration, while AI techno-complexity impaired recovery by thwarting competence. These findings suggest organizations must both mitigate AI-induced frustration and cultivate AI-driven mastery to protect employee well-being.