Generative AI tools and career burnout: The chain mediating effect of technology stress perception on turnover intention among young tech talents

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Abstract
This study investigates the chain mediating effect of technology stress perception and career burnout on the relationship between generative AI tools usage and turnover intention among young tech talents. A cross-sectional survey design was employed with 683 technology professionals aged 21-35, using structural equation modeling to analyze the proposed sequential pathway. Generative AI tools usage significantly influences turnover intention through a sequential pathway: AI tools usage positively affects technology stress perception (β = .36, p < .001), which contributes to career burnout (β = .53, p < .001), ultimately increasing turnover intention (β = .49, p < .001). This chain mediation effect was significant (indirect effect = .094, 95% CI [.071, .124]), explaining 67.1% of the total effect. The findings extend technostress theory to generative AI contexts and establish that technology self-efficacy and organizational support function as protective factors by mitigating technology stress and burnout, respectively. Practical implications: organizations implementing AI technologies should adopt strategic approaches focusing on reducing technology stress and preventing burnout to maintain workforce stability during technological transitions.

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