The impact of AI anxiety on employees' work passion: A moderated mediated effect model
The application of artificial intelligence technology has significantly enhanced the operational efficiency of companies, but it has also brought pressure related to job replacement and technological upgrading, leading to anxiety among employees regarding artificial intelligence. This kind of anxiety has a profound impact on employees' work passion, yet currently, there are relatively few researches on this area, making further exploration necessary. This study obtained necessary data by distributing questionnaires to 430 employees in manufacturing companies and conducted empirical analysis to examine how employees' anxiety about artificial intelligence affects their work passion. The results show that anxiety about job replacement and anxiety about learning both diminish employees' work passion, and emotional exhaustion plays a partially mediating role in this process. In addition, service-oriented leadership and learning goal orientation have different moderating effects in the relationship. The findings of this study provide a reference for companies to develop strategies to alleviate the negative impact of employees' anxiety about artificial intelligence on their work passion and enhance the effectiveness of artificial intelligence applications.
Authors
- Xinqiang Chen (ORCID: https://orcid.org/0009-0006-4947-5789)
- Jiangjie Chen (ORCID: https://orcid.org/0000-0002-2613-0386)
- Xiue Zhang (ORCID: https://orcid.org/0000-0002-1758-9291)
- Jin Ke (ORCID: https://orcid.org/0000-0001-8887-3743)
Institutions
- Huaqiao University (CN)
- Jilin University of Finance and Economics (CN)
- Jilin University (CN)
- Xiamen University of Technology (CN)
Publication Details
- Journal
- Acta Psychologica
- Published
- 2025-09-03
- DOI
- https://doi.org/10.1016/j.actpsy.2025.105487
- Citations
- 1
- Primary Topic
- Cyberloafing and Workplace Behavior
- Type
- article
- Field-Weighted Citation Impact
- 5.59
Funders
- Xiamen University of Technology