How Can Teams Benefit From AI Team Members? Exploring the Effect of Generative AI on Decision-Making Processes and Decision Quality in Team–AI Collaboration

Human teams with distributed knowledge can make high-quality decisions but often fail due to decision-making asymmetries.As AI team members become integrated collaborators, understanding how AI can reduce these decision-making asymmetriesis essential. However, little is known about how AI team members can reduce these asymmetries and whether new AI-specificasymmetries emerge from team–AI collaboration. Building on the information asymmetries model, we conducted an exploratoryexperiment with 215 individuals across 81 teams performing a hidden profile task under three knowledge configurations: (1)human teams with asymmetric knowledge, (2) teams collaborating with AI with centralized knowledge, and (3) teams collab-orating with AI with asymmetric knowledge. Our results show that teams with centralized AI knowledge make more accuratedecisions than human teams due to reduced decision-making asymmetries, trust in AI, beneficial AI information processing,and a balanced AI collaboration focus. In contrast, teams with asymmetric AI knowledge show only moderate reductions indecision-making asymmetries. Moreover, due to emerging AI-specific asymmetries—such as mistrust, nonbeneficial AI infor-mation processing, and a critical AI collaboration focus—these teams fail to outperform human teams. We integrated our find-ings into process models that illustrate how successful team–AI collaboration depends on effective teamwork between humanand AI members.