Teaming Up with Artificial Agents in Non-routine Analytical Tasks

Although AI systems are becoming increasingly common in the workplace, research on their integration into human teams remains limited. In particular, little is known about how the embodiment of artificial agents shapes collaboration and performance in non-routine analytical tasks. To address this gap, we examine how different degrees of embodiment affect team performance and conversational dynamics in a real-life escape room. Teams composed of either three humans or two humans and an artificial agent (a Box, an Avatar, or a hyper-realistic humanoid) worked together to escape the room within a time limit. Our findings show that artificial agents have an uneven impact on team outcomes, with some mixed human–AI teams performing exceptionally well and others markedly worse. Human-only teams, by contrast, display more consistent performance: they are more likely to complete all tasks successfully, although they take longer and commit more errors. We also document a suggestive non-linear relationship between embodiment and team performance. Teams interacting with more embodied agents display conversational patterns that more closely resemble human–human dialogue. Together, these findings show that embodied AI shapes collaboration in complex ways, reinforcing evidence that social cues critically guide teamwork dynamics.