Unveiling Team Emergent States in the Age of Human-AI Teaming

Artificial intelligence (AI) is increasingly becoming a part of organizational teams, reshaping teamwork. This study explores team emergent states (team cohesion, team identification, team psychological safety) in Human-AI teams (HATs) compared to purely human teams (HTs). In a laboratory experiment, participants (final N = 67 teams; 134 individuals) completed two successive work-related tasks over two rounds (20 min each). The first round involved two human teammates. The second round introduced a third teammate – either another human (resulting in HTs) or an AI (resulting in HATs). Following the Social Identity Theory, we expected that HATs would exhibit lower levels of team emergent states. Team cohesion and identification were lower in HATs and we found mediating effects of self-rated team performance and team trust. There was no significant difference in perceived team psychological safety. Participants in HATs identified less with the AI than with the human teammate. These findings suggest that traditional team dynamics might not be directly applied to HATs, emphasizing the need for further research on team dynamics to understand the unique impact of AI on teamwork. This research advances our understanding of the implications of integrating AI into teams and provides practical insights for implementing AI while maintaining effective teamwork.