When AI Becomes My Teammate: Unpacking How Employees Perceive and Collaborate With Gendered AI Teammates

ABSTRACT While artificial intelligence (AI) is increasingly embedded into teams, how employees perceive and collaborate with AI teammates, especially those with gender characteristics, remains an urgent but underexplored question. This research integrates social perception theory and social role theory to investigate how employees socially differentiate AI from human teammates and how these social perceptions consequently shape employee–AI cooperation. Across three studies, including a vignette‐based experiment ( N 1 = 163), a fictional interactive experiment ( N 2 = 465), and a preregistered field survey ( N 3 = 155), we found that in general, employees perceived AI teammates as more competent but less warm than human teammates. This competence advantage of AI enhanced employee cooperation with AI, but its perceived lack of warmth hindered cooperation. Moreover, AI teammates designed with female‐like characteristics compensated for this warmth deficit (Study 1), but simultaneously diminished AI's competence advantage over humans (Studies 2 and 3). Conversely, AI teammates designed with male‐like characteristics amplified AI's competence advantage (Studies 2 and 3) but exacerbated its absence of warmth (Study 1). Finally, these gendered perceptions of AI influenced employee–AI cooperation in paradoxical ways. Overall, our research underscores that incorporating AI into teams, especially ascribing AI gender characteristics, is a mixed blessing for human–AI teamwork.

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Publication Details

Journal
Journal of Organizational Behavior
Published
2025-11-06
DOI
https://doi.org/10.1002/job.70038
Citations
1
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
2.48
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article

When AI Becomes My Teammate: Unpacking How Employees Perceive and Collaborate With Gendered AI Teammates

Wei He, Yidong Tu, Jiahui Chen, Jing Li et al.
1 citations
Journal of Organizational Behavior
AI in Service Interactions
2.48
article

When AI Becomes My Teammate: Unpacking How Employees Perceive and Collaborate With Gendered AI Teammates

Wei He, Yidong Tu, Jiahui Chen, Jing Li, Chang-Jun Li
article en
1 citations

Abstract

ABSTRACT While artificial intelligence (AI) is increasingly embedded into teams, how employees perceive and collaborate with AI teammates, especially those with gender characteristics, remains an urgent but underexplored question. This research integrates social perception theory and social role theory to investigate how employees socially differentiate AI from human teammates and how these social perceptions consequently shape employee–AI cooperation. Across three studies, including a vignette‐based experiment ( N 1 = 163), a fictional interactive experiment ( N 2 = 465), and a preregistered field survey ( N 3 = 155), we found that in general, employees perceived AI teammates as more competent but less warm than human teammates. This competence advantage of AI enhanced employee cooperation with AI, but its perceived lack of warmth hindered cooperation. Moreover, AI teammates designed with female‐like characteristics compensated for this warmth deficit (Study 1), but simultaneously diminished AI's competence advantage over humans (Studies 2 and 3). Conversely, AI teammates designed with male‐like characteristics amplified AI's competence advantage (Studies 2 and 3) but exacerbated its absence of warmth (Study 1). Finally, these gendered perceptions of AI influenced employee–AI cooperation in paradoxical ways. Overall, our research underscores that incorporating AI into teams, especially ascribing AI gender characteristics, is a mixed blessing for human–AI teamwork.

Journal of Organizational Behavior
Wuhan University (CN), Hubei University Of Economics (CN), Wuhan Business University (CN), Nanjing University (CN)
Openalex Percentile: Top 8%
AI in Service Interactions
2.48
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