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◆ Journal of Innovation & Knowledge2025-10-19· Structural equation modeling

Generative AI and employee well-being: Exploring the emotional, social, and cognitive impacts of adoption

Serena Filippelli, Alina Irina Popescu, Saverino Verteramo, Mario Tani, Vincenzo Corvello

原始摘要(英文原文)· Original abstract
Generative artificial intelligence (GenAI) is increasingly recognized as a transformative technology that is reshaping organizational processes, individual work practices, and workplace interactions. While its benefits for efficiency and productivity are widely acknowledged, its impact on employee well-being remains largely underexplored. This study investigates the relationship between GenAI adoption and three dimensions of employee well-being: emotional, social, and cognitive. Drawing on the job demands-resources (JD-R) model and social cognitive theory, we propose a conceptual framework in which the GenAI intensity of adoption mediates the relationship between employees’ attitudes toward the technology and their well-being. By analyzing survey data from approximately 130 knowledge workers and analyzing it through partial least squares structural equation modeling (PLS-SEM), our findings reveal that a positive attitude toward GenAI significantly enhances its adoption, whereas a negative attitude does not necessarily prevent usage. Furthermore, the extent of GenAI adoption influences all three dimensions of well-being, with team cohesion acting as a mediating factor. These results contribute to the literature on workplace well-being and technology adoption by offering theoretical and managerial insights into the complex relationship between AI integration and employee experience.
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