When Misunderstanding Meets Artificial Intelligence: The Critical Role of Trust in Human-AI and Human-Human Team Communication and Performance

Chen Na^*Xinyue Zhang

• College of Economics and Management, Beijing University of Chemical Technology, Beijing, China

As artificial intelligence (AI) technologies become deeply embedded in organizational teamwork, managing communication breakdowns in human – AI collaboration has emerged as a central managerial challenge. While AI-empowered teams often benefit from enhanced efficiency, misunderstandings — particularly those caused by AI agents during information exchange — may undermine team trust and impair performance. However, the underlying mechanisms remain underexplored. Grounded in evolutionary psychology and trust theory, this study adopts a 2 (team type: human – AI vs. human – human) × 2 (misunderstanding type: information omission vs. ambiguous expression) experimental design with 126 valid participants. Using a task scenario involving the collaborative creation of a popular science social media column, the participants were asked to jointly complete a planning and writing task with their assigned teammate. The results show that information omissions caused by AI agents significantly reduce team trust, thereby hindering communication efficiency and overall performance. In contrast, the negative impact of ambiguous expressions is moderated by the level of team trust — high-trust environments exhibit greater adaptability and resilience. Further moderated mediation analyses reveal that team type shapes the dynamic pathway from misunderstanding to trust and performance. This research deepens the theoretical understanding of misunderstanding management in human–AI teams and offers practical insights for AI system optimization and effective human–machine collaboration.