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

ABSTRACT 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 asymmetries is essential. However, little is known about how AI team members can reduce these asymmetries and whether new AI‐specific asymmetries emerge from team–AI collaboration. Building on the information asymmetries model, we conducted an exploratory experiment 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 collaborating with AI with asymmetric knowledge. Our results show that teams with centralized AI knowledge make more accurate decisions 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 in decision‐making asymmetries. Moreover, due to emerging AI‐specific asymmetries—such as mistrust, nonbeneficial AI information processing, and a critical AI collaboration focus—these teams fail to outperform human teams. We integrated our findings into process models that illustrate how successful team–AI collaboration depends on effective teamwork between human and AI members.