How could AI-driven digital monitoring affect employee AI usage: a study based on social information processing theory

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Authors: Yunjian Li, Jie He, Yanming Sun
Cited by: 2
References: 66

Abstract

As AI-driven digital monitoring becomes increasingly prevalent in workplace management, employee AI usage has become essential for successful organisational implementation. However, the relationship between such monitoring and employee AI usage remains underexplored. Drawing on social information processing theory, this study examines how AI-driven digital monitoring influences employee AI usage by investigating the mediating roles of social pressure to use AI and perceived AI capability. Through a preliminary survey of 143 manufacturing employees, we developed a measure of AI-driven digital monitoring and subsequently tested the conceptual model with 225 manufacturing employees. Results indicate that perceived social pressure and AI capability sequentially mediate the effect of work-behaviour monitoring on employee AI usage. In contrast, only social pressure mediates the relationship between workplace digital monitoring and AI usage. By revealing these distinct psychological processes, this study provides new insights into the mechanisms through which AI-driven digital monitoring influences AI usage. The findings offer theoretical and practical implications for the integration of AI in human resource management.

Fields of Study & Subjects

AI and HR Technologies AI in Service Interactions Robotic Process Automation Applications

Publication details

Journal / source
Behaviour and Information Technology
Publisher
Informa UK Limited
Pages
1–18
Publication date
22 January 2026
Language
EN