Stress and self-efficacy under artificial intelligence disruption: A mixed-methods study on the usage of artificial intelligence among Finnish workers

Abstract

Rapid workplace integration of artificial intelligence (AI) is reshaping work practices and challenging employees’ self-efficacy and well-being. This mixed-methods study examines these experiences using national survey data ( N = 2109) and qualitative interviews ( N = 54) with Finnish workers. Frequent AI use, AI-induced identity threat, and organizational AI deployment are associated with higher AI strain, whereas AI self-efficacy relates to frequent use, positive AI attitudes, and subjective well-being. Identity threat moderated several of these associations, highlighting the role of professional identity in AI-related experiences. Analysis drawing on Greimas’ semiotic modalities (must, can, know, and want) explains how these patterns are interpreted and negotiated in practice, revealing tensions between perceived self-efficacy and pressures to integrate AI. AI use was often described as voluntary. However, participants anticipated increasing competence demands and responsibility. The findings emphasize the need for organizational strategies that address identity-related challenges and support employee well-being in AI-driven work transformations.