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The impact of generative AI use on employees' psychological distress: a moderated mediation model
Meng Liu1,2, Yang Li1, Jing Li1,2
1School of Management, Tianjin University of Commerce, Tianjin, China.
Introduction:
With the widespread adoption of generative artificial intelligence (Gen AI) in the workplace, concerns have emerged about whether employees experience psychological distress alongside efficiency improvements.
Methods:
Based on the Stimulus-Organism-Response (SOR) framework, we developed a moderated mediation model and used survey data from 424 Chinese employees to examine the relationship between Gen AI use and employees' psychological distress. We tested dual mediating pathways (job insecurity and workplace loneliness) and two boundary conditions (information literacy and AI ethical risk perception).
Results:
Our study reveals that Gen AI use is significantly associated with psychological distress via the dual mediating paths of job insecurity and workplace loneliness. Employees' information literacy can mitigate the relationship between Gen AI and job insecurity, and further moderate the mediating effect on psychological distress. Conversely, AI ethical risk perception strengthens the relationship between Gen AI and workplace loneliness, and is further associated with psychological distress via a moderated mediation effect.
Discussion:
Our study contributes to the theoretical understanding and empirical evidence regarding the relationship between Gen AI and employees' psychological distress. It also provides practical recommendations for managers and employees on how to interact effectively with Gen AI tools.
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