From AI use to positive functioning: The roles of trust and need satisfaction

Abstract In this empirical contribution to Group. Interaction. Organization. (GIO), we examined how the incorporation of artificial intelligence (AI) into everyday work processes is associated with employee well-being and engagement focusing on the psychological mechanisms of trust in AI and basic need satisfaction. Drawing on Self-Determination Theory and trust-in-technology research, we investigated whether different AI use patterns are associated with workplace well-being and work engagement via trust in AI and the satisfaction of autonomy, competence, and technology-related relatedness needs. A cross-sectional survey of N = 379 employees (predominantly young employees with limited work experience) using AI at work assessed AI use patterns, trust, need satisfaction, PERMA well-being, and work engagement. Structural equation modeling showed partial support for the proposed model. Problem-solving AI use was positively associated with trust in AI, and trust in AI was positively associated with autonomy, competence, and relatedness to technology. However, none of these needs was associated with workplace well-being or work engagement. These findings suggest that trust is central for experiencing AI as supportive, but that need satisfaction during AI use may not meaningfully relate to broader employee functioning. Given the cross-sectional design, the findings should be interpreted as evidence for associations consistent with the proposed model rather than as support for temporal or causal processes. The study highlights the importance of task characteristics in AI implementation and outlines directions for future longitudinal research on domain-specific outcomes and boundary conditions.