Working with AI: The Association between Generative AI Usage and Well-Being among Knowledge Workers
Marie Lutter, Sophie Grothe · DiVA (Linnaeus University) · 2026
Artificial intelligence (AI) is reshaping the global workforce, bringing profound changes to both workplace and academic environments. Understanding its psychological impact, particularly on knowledge workers, is increasingly important as both benefits and challenges are experienced. This thesis explored the relationship between generative AI usage and well-being among knowledge workers. We addressed two research questions: Firstly, (RQ1) whether generative AI usage is associated with well-being, self-efficacy, and stress. In accordance with this, when accounting for potential control variables such as age, gender, workload, and learning motivation, we used a directed acyclic graph (DAG). Secondly, (RQ2) whether the context of AI use (academia/work vs. leisure time) modifies the association with well-being. Using a cross-sectional online survey (N = 164), we found no significant association between generative AI usage and well-being, self-efficacy, or stress, regardless of use context or demographic and work-related control variables. These findings suggest that the frequency of generative AI usage alone does not meaningfully predict psychological outcomes among knowledge workers. Rather, the present findings indicate that the psychological outcomes may depend more on contextual and individual factors, including how and why the technology is used, employees´ attitudes toward it, its perceived usefulness, existing workload, and learning motivation. The implications highlight the necessity for a nuanced approach to AI integration, recognising that generative AI can act as both a resource and a demand in the workplace. In conclusion, future longitudinal and experimental studies are needed to clarify causal relationships and long-term effects.