Uneven but Better? Unequal AI Access Leads to Greater Dominant Style Differences and Enhanced Team Communication Effectiveness

The widespread use of generative AI (GenAI) is seen as beneficial for team collaboration, yet full access for all members is often impractical in real-world settings. This study investigates how varying levels of GenAI integration influence team communication dynamics: no access (team members do not use AI), unequal access (only some members use AI), and full access (all members use AI). In a laboratory experiment with 60 two-person teams, all teams first performed a task without AI, then were randomly assigned to either the unequal or full access condition. Under unequal access, AI users adopted more dominant communication styles, creating greater style differences that, in turn, enhanced team communication effectiveness compared to both no access and full access. This research provides theoretical insights into the effects of varied GenAI integration structures on human-AI collaboration and offers practical guidance for optimizing team design in human-agent systems.