ORIGINAL RESEARCH article
Front. Psychol.
Sec. Organizational Psychology
This article is part of the Research TopicDigital Solutions for Workplace Conflict: Enhancing Mental Health and Job PerformanceView all 4 articles
The Forgotten Middle: How Moderate Self-Efficacy Amplifies the Threat of AI through Job Insecurity
Provisionally accepted- 1Anhui Wenda University of Information Engineering, Hefei, China
- 2Sunway University, Bandar Sunway, Malaysia
- 3University of Malaya, Kuala Lumpur, Malaysia
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Artificial intelligence (AI) has sparked a paradox in organizational behavior research: while it promises productivity gains, it simultaneously generates psychological strain and inconsistent performance outcomes. Drawing on Conservation of Resources (COR) theory and technology empowerment theory, this study investigates how AI adoption affects employee job performance through job insecurity and how self-efficacy shapes this relationship in a nonlinear way. Using multi-source paired data from 392 employees and their supervisors in China's cross-border e-commerce sector, the results reveal that AI's positive technological empowerment is fully offset by its negative psychological threat, forming a suppression structure. Job insecurity mediates the relationship between AI application and performance, while self-efficacy moderates this effect in an inverted U-shaped manner—employees with moderate self-efficacy experience the highest insecurity and the strongest indirect negative effect. These findings advance COR theory by conceptualizing self-efficacy as a finite resource and highlight how psychological mechanisms determine whether AI empowers or undermines employees.
Keywords: artificial intelligence, Job Insecurity, self-efficacy, suppression-based mediation, curvilinear moderation, Employee performance
Received: 28 Oct 2025; Accepted: 02 Dec 2025.
Copyright: © 2025 Liu and Ye. 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: Zijian Ye
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
