ArticleSSM - population health2026
Social comparison contributes to work exhaustion in the context of workplace AI use: A three-wave follow-up study of Finnish workers.
Article in SSM - population health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: The rise of artificial intelligence (AI) is transforming work tasks and social relations within organizations. Work exhaustion is increasing, and AI may heighten employees' sense of adaptability and social comparison. This three-wave longitudinal study examines employees' work exhaustion as an outcome of AI use at work, perceived AI readiness, and social comparison tendencies. Methods: Data were drawn from a national survey of employed adults aged 18-65 years in Finland. Baseline data were collected in fall 2024 (N = 2109; 50% men; mean age 42·6 years), with biannual follow-ups. Work exhaustion (Maslach Burnout Inventory), social comparison orientation (INCOM), perceived AI readiness, and AI use at work were assessed. Within-between and multilevel mixed effects regression models were used to estimate within- and between-person associations over time. Findings: Frequent AI use at work was not associated with work exhaustion, whereas social comparison tendency showed robust associations with greater exhaustion at both the within- (β = 0·02, [95% CI 0·01 to 0·04], P = 0·001) and between-person (B = 0·20, [95% CI 0·15 to 0·25], P < 0·001) levels. Workers with higher perceived AI readiness reported lower exhaustion between individuals in the first model (B = -1·41, [95% CI -2·17 to -0·64], P <0·001) and within individuals (B = -0·02, [95% CI -0·04 to -0·01], P = 0·002) and between individuals in the second model (B = -0·16, [95% CI -0·21 to -0·11], P <0.001). No interaction effects were observed between AI use at work and AI readiness or social comparison in the primary models. However, exploratory analyses suggested that among employees with high social comparison tendencies, frequent AI use at work was associated with elevated exhaustion (B = 0·05, [95% CI 0·00 to 0·09], P = 0·035). Interpretation: Findings suggest that individual psychosocial dispositions may play an important role in experiences of exhaustion in AI-augmented workplaces. At the same time, perceived AI readiness may function as a personal resource associated with lower exhaustion.
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