ORIGINAL RESEARCH article
Front. Psychol.
Sec. Quantitative Psychology and Measurement
Volume 16 - 2025 | doi: 10.3389/fpsyg.2025.1603393
This article is part of the Research TopicTechnologies for Mental Health: Toward a Computational Psychology?View all 3 articles
Impact of AI Workplace Anxiety on Life Satisfaction Among Service Industry Employees: Exploring Mediating and Moderating Factors
Provisionally accepted
- 1Chongqing University of Arts and Sciences, Chongqing, Chongqing, China
- 2Xihua University, Chengdu, China
- 3Shenzhen BEEPLUS Technology Co., Ltd., SHENZHEN, China
- 4Chongqing Digital Economy Talent Market Yongchuan Market, chongqing, China
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Objective:To investigate the impact of artificial intelligence (AI) job anxiety on service industry employees’life satisfaction and offer insights to mitigate its negative effects.Design:Cross-sectional study. Methods:A questionnaire survey was conducted among 600 service employees via the Questionnaire Star platform, with 549 valid responses. PROCESS Models 4 and 7 were used to test mediation and moderated mediation effects. Results:Life satisfaction was above average. AI job anxiety significantly and negatively predicted life satisfaction (t = -3.905, P < 0.001), fully mediated by negative emotions (β = -0.161, 95% CI = -0.219 ~ -0.107). Social support moderated the effect of AI anxiety on negative emotions (β = -0.098, t = -3.455, P < 0.01). Conclusion:AI job anxiety reduces employees’ life satisfaction. This effect can be alleviated by enhancing vocational training, emotional regulation, and social support systems.
Keywords: artificial intelligence job anxiety, life satisfaction, Negative emotions, social support, Service industry employees
Received: 31 Mar 2025; Accepted: 18 Jul 2025.
Copyright: © 2025 Hu, Feng, CHEN, XU, ZHANG and hao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Zhao Feng, Xihua University, Chengdu, China
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