Post-Public AI: Research in Groups and Teams

The 2022 public release of ChatGPT marked a key moment in human interaction with artificial intelligence (AI), driving the widespread adoption of generative AI tools. This special issue examines how AI diffusion demands a reconceptualization of group and team research. We propose a distinction between pre- and post-public AI eras, noting that today’s teams increasingly include members with everyday AI experience. Building on Katzenbach and Smith’s classic definition of teams, we stress the need to integrate human-AI dynamics, which introduce new complexities in team composition, complementary skills, shared purpose, and accountability. We advocate for openness to diverse approaches, greater methodological innovation, and interdisciplinary partnerships to keep pace with AI-driven change. The issue features two contributions: one examining how AI types shape trust and attention, another assessing AI-driven methods for analyzing team communication. We hope this editorial sparks a broader conversation to advance group scholarship in the post-public AI era.

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Institutions

Publication Details

Journal
Small Group Research
Published
2025-08-14
DOI
https://doi.org/10.1177/10464964251363458
Citations
2
Primary Topic
Team Dynamics and Performance
Type
article
Field-Weighted Citation Impact
4.88
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article

Post-Public AI: Research in Groups and Teams

Katerina Bezrukova, Terri L. Griffith
2 citations
Small Group Research
Team Dynamics and Performance
4.88
article

Post-Public AI: Research in Groups and Teams

Katerina Bezrukova, Terri L. Griffith
article en
2 citations

Abstract

The 2022 public release of ChatGPT marked a key moment in human interaction with artificial intelligence (AI), driving the widespread adoption of generative AI tools. This special issue examines how AI diffusion demands a reconceptualization of group and team research. We propose a distinction between pre- and post-public AI eras, noting that today’s teams increasingly include members with everyday AI experience. Building on Katzenbach and Smith’s classic definition of teams, we stress the need to integrate human-AI dynamics, which introduce new complexities in team composition, complementary skills, shared purpose, and accountability. We advocate for openness to diverse approaches, greater methodological innovation, and interdisciplinary partnerships to keep pace with AI-driven change. The issue features two contributions: one examining how AI types shape trust and attention, another assessing AI-driven methods for analyzing team communication. We hope this editorial sparks a broader conversation to advance group scholarship in the post-public AI era.

Small Group ResearchVol. 56(5)
Simon Fraser University (CA), University at Buffalo, State University of New York (US)
Openalex Percentile: Top 5%
Team Dynamics and Performance
4.88
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