Understanding employee behavioral adaptation to AI-based job monitoring through system justification theory

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Authors: Yibin Li, Zhuo-Jie Yang, Tung‐Ju Wu
Cited by: 1
References: 54

Abstract

AI-based job monitoring is crafting the workplace nowadays. Based on the system justification theory, we explored how AI-based job monitoring, acting as a kind of organizational management policy, reduces employees’ withholding effort. We conducted two studies to explore and verify our theoretical model. In study 1, we interviewed 25 employees from an AI-applied enterprise to explore how AI-based job monitoring has been justified and its effect on employees. And for study 2 ( N = 351), we further collected three-wave data to verify our findings of Study 1. As a result, we concluded that AI-based job monitoring functions as a management system that the whole organization defends despite its potential adverse influence. Meanwhile, surveillance anxiety mediates the relationship between AI-based job monitoring and withholding effort out of concern for privacy invasion. While employees’ psychological entitlement hinders the process of justification and buffers the decline of withholding effort. Consequently, our study introduces system justification theory into management research in a micro view and illustrates the particular context. The findings would instruct enterprises to promote the implementation of new system during digital transformation.

Fields of Study & Subjects

AI in Service Interactions Ethics and Social Impacts of AI AI and HR Technologies

Publication details

Journal / source
Humanities and Social Sciences Communications
Publisher
Springer Science and Business Media LLC
Volume
13
Issue
1
Publication date
17 June 2026
Language
EN