Affiliation or alienation? How does AI awareness affect employees’ interaction with co-workers

Purpose The purpose of this study is to address this research gap by shifting attention from the individual consequences of AI awareness to its interpersonal implications. While workplaces value interactions between co-workers, research on artificial intelligence (AI) awareness has focused on its impact on employees themselves, to the detriment of its impact on interactions among colleagues. Through a longitudinal tracking study and based on social information processing (SIP) theory and the social affiliation literature, this study explores the impact of employees’ AI awareness on their attitudes and behaviours. Design/methodology/approach The theoretical model was tested using three waves of data from 298 participants in China. Findings AI awareness can increase employees’ need for affiliation with colleagues and reduce their sense of alienation. AI awareness promotes helping behaviour through the need for affiliation but reduces helping behaviour through alienation. A higher level of AI dependence corresponds to stronger relationships between AI awareness and the need for affiliation and between AI awareness and alienation. Practical implications Organizations should strive to improve employees’ positive perceptions of AI, focus on their experiences of using AI in daily communication, strengthen their need for affiliation and reduce their feelings of alienation. Originality/value Based on SIP theory and the social affiliation literature, this study provides a comprehensive explanation of how employees’ AI awareness affects their attitudes and behaviours towards their colleagues, thereby deepening our comprehensive understanding of AI awareness.

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Publication Details

Journal
Chinese Management Studies
Published
2026-09-09
DOI
https://doi.org/10.1108/cms-06-2025-0621
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Affiliation or alienation? How does AI awareness affect employees’ interaction with co-workers

Tao Wang, Huaying Wang, Hao Zeng
Chinese Management Studies
Ethics and Social Impacts of AI
article

Affiliation or alienation? How does AI awareness affect employees’ interaction with co-workers

Tao Wang, Huaying Wang, Hao Zeng
article en

Abstract

Purpose The purpose of this study is to address this research gap by shifting attention from the individual consequences of AI awareness to its interpersonal implications. While workplaces value interactions between co-workers, research on artificial intelligence (AI) awareness has focused on its impact on employees themselves, to the detriment of its impact on interactions among colleagues. Through a longitudinal tracking study and based on social information processing (SIP) theory and the social affiliation literature, this study explores the impact of employees’ AI awareness on their attitudes and behaviours. Design/methodology/approach The theoretical model was tested using three waves of data from 298 participants in China. Findings AI awareness can increase employees’ need for affiliation with colleagues and reduce their sense of alienation. AI awareness promotes helping behaviour through the need for affiliation but reduces helping behaviour through alienation. A higher level of AI dependence corresponds to stronger relationships between AI awareness and the need for affiliation and between AI awareness and alienation. Practical implications Organizations should strive to improve employees’ positive perceptions of AI, focus on their experiences of using AI in daily communication, strengthen their need for affiliation and reduce their feelings of alienation. Originality/value Based on SIP theory and the social affiliation literature, this study provides a comprehensive explanation of how employees’ AI awareness affects their attitudes and behaviours towards their colleagues, thereby deepening our comprehensive understanding of AI awareness.

Chinese Management Studies
Jiangxi Science and Technology Normal University (CN), Jiangxi University of Finance and Economics (CN)
Openalex Percentile: Top 7%
Ethics and Social Impacts of AI
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