Open Access

ARTICLE

How and When Organizational Artificial Intelligence Adoption Impacts Employees’ Well-Being

Yuchao Pan^*

Economics and Management School, The Department of Business Administration, Wuhan University, Wuhan, 430072, China

* Corresponding Author: Yuchao Pan. Email:

International Journal of Mental Health Promotion 2025, 27(11), 1769-1780. https://doi.org/10.32604/ijmhp.2025.070147

Received 09 July 2025; Accepted 11 October 2025; Issue published 28 November 2025

Abstract

Objectives: While organizations are increasingly adopting artificial intelligence (AI), its effects on employees’ well-being remain poorly understood. Drawing on social cognitive theory, this study aimed to examine the underlying mechanism through which organizational AI adoption influences employees’ well-being. Methods: A two-wave time-lagged research design was conducted with 262 Chinese employees employing a voluntary and anonymous survey. The survey included measures of organizational AI adoption, AI use anxiety, job insecurity, subjective well-being, and psychological well-being. The data were analyzed using SPSS 26.0 software and macro PROCESS. Results: The moderation analysis revealed that AI use anxiety moderated the association between organizational AI adoption and job insecurity (b = 0.19, standard error [SE] = 0.04, p < 0.001), indicating that organizational AI adoption was positively related to job insecurity when AI use anxiety was higher. The moderating mediation analysis further revealed that the indirect effect of organizational AI adoption on employees’ well-being via job insecurity was negative (for subjective well-being, moderated mediation index = −0.05, SE = 0.03, 95% CI = [−0.103, −0.005]; for psychological well-being, moderated mediation index = −0.04, SE = 0.02, 95% CI = [−0.089, −0.007]), indicating that organizational AI adoption would impair employees’ well-being by increasing job insecurity for employees with a higher level of AI use anxiety. Conclusions: AI use anxiety acts as a critical moderator in the link between organizational AI adoption and employee well-being. The finding supports the notion that a wide variety of boundary conditions may influence how individuals react to AI filling roles typically held by humans.

---

Keywords

---