How does human-AI interaction affect employees' workplace procrastination?

Jia-Min Li, Lan-Xia Zhang and Meng-Yu Mao

Technological Forecasting and Social Change, 2025, vol. 212, issue C

Abstract: Based on the conservation of resources (COR) theory, this study examined the mechanisms by which human-AI interaction influences employees' workplace procrastination and the mediating role of boredom and the moderating role of core self-evaluation. Two studies were conducted to test the hypothesized model. In Study 1, human-AI interactions were categorized into enhanced and impeded. Enhanced human-AI interaction is the degree to which the employee perceives that the employee is leading the work and that the AI assists the work, whereas impeded human-AI interaction is the degree to which the employee perceives that the AI is leading the work and that the employee assists the work. We developed a two-dimensional human-AI interaction scale with eight items. In Study 2, we tested our hypotheses by collecting data from 411 questionnaires in China. Both types of human-AI interaction significantly affected boredom and workplace procrastination. Boredom mediated both types of human-AI interaction and workplace procrastination. Core self-evaluation not only moderated the effects of both types of human-AI interaction on boredom but also moderated the mediating role of boredom. This study has significant implications for both the theoretical understanding of human-AI interaction and its practical applications in organizational management.

Keywords: Human-AI interaction; Enhanced human-AI interaction; Impeded human-AI interaction; Workplace procrastination; Core self-evaluation (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:212:y:2025:i:c:s0040162524007492

DOI: 10.1016/j.techfore.2024.123951

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