AI as an Agent and Collaborative Space: Exploring the role of generative AI in small group synchronous and asynchronous collaborative dynamics

AI as an Agent and Collaborative Space. A qualitative study by Haowei Xu, Ahmed Kharrufa, Ellis Solaiman & Vasilis Vlachokyriakos (2026) examining how generative AI shapes small-group collaboration through observations and interviews with 27 higher-education students. Through a distributed cognition lens, the study finds a stark contrast: in synchronous settings with a single shared GenAI interface, teams maintain shared awareness, co-construct prompts, treat the chat as shared external memory, and openly negotiate AI's role — whereas in asynchronous teamwork GenAI is used individually, with outputs selectively rewritten or "de-labelled" before being shared, making AI's influence on decisions opaque and harder to trace. The paper proposes a GenAI-Supported Cooperative Work (GSCW) perspective, framing GenAI as both a configurable agent (from individual assistant to team member) and an interactive collaborative space.

Overview

GenAI systems are designed for single-user interaction, yet they are increasingly integrated into collaborative work. This study asks how introducing GenAI influences collaborative dynamics — information flow, role negotiation, and decision-making — in small-group teamwork, and what new collaboration challenges it raises. The distributed cognition lens reframes GenAI as a cognitive participant distributed across people, tools, and environment.

Method

• Observation study: 18 students in six groups of three, working synchronously (3 in-person, 3 online via Microsoft Teams) on designing a cultural educational game with a single shared ChatGPT-4 interface over ~45 minutes, followed by reflection.
• Interviews: 9 additional semi-structured interviews (~45 min) capturing asynchronous, everyday GenAI use in teamwork.
• Analysis: Qualitative thematic coding across three collaborative-dynamics dimensions — information flow, role negotiation, decision-making — plus GenAI as a collaborative space.

Key findings

• Access configuration shapes information flow. With a shared, visible interface, teams co-constructed "collective prompts" and ran a recurring surface–evaluate–embed cycle, sustaining common ground. In asynchronous settings, private, fragmented prompting and output de-labelling produced opaque, privatised information flows that raised the cost of maintaining a shared cognitive model.
• Awareness must extend to the AI. GenAI is cognitively involved but contextually unaware of the team's shifting focus — a paradox that forces teams to constantly repair drift between the AI's limited awareness and the actual collaborative trajectory. Future systems need AI aware of group state and, with multiple agents, aware of each other.
• Roles are negotiated, not fixed. GenAI's role shifted from subordinate assistant to contested teammate depending on context and proactivity expectations; teams debated and constrained AI influence to ensure alignment and accountability.
• Design direction — permeable boundaries with directional context. Team-level AI should pass shared context into personal AI spaces, but insights generated privately should not auto-flow back to the group; humans stay in control of what becomes part of the shared record.

Practical implications

• Surface AI contributions. The surface–evaluate–embed cycle is a practical pattern: explicitly highlight, verify, and embed AI outputs to anchor shared attention and memory.
• Design for both synchronous and asynchronous modes. Collaborative GenAI systems should combine private and shared access and offer shared spaces that support group memory, moving beyond one-to-one interaction models.
• Instructors: be aware that asynchronous group GenAI use can fragment transparency; encourage practices that surface AI inputs for collective negotiation.

Connected Concepts

• Collaborative Learning — small-group teamwork as the context
• Distributed Cognition — the theoretical lens; GenAI as a distributed cognitive participant
• Human AI Collaboration — negotiating GenAI's role in group work
• Conversational AI — chat-based GenAI as agent and space

Connected Articles

• GenAI Group Writing Strategies 2026 — GenAI and group writing strategies
• GenAI Counter Learner Groupthink 2025 — GenAI countering learner groupthink
• Adaptive AI Scaffold Collaborative Problem Solving 2026 — adaptive AI scaffolding in collaborative problem-solving
• AI Chatbot Collective Efficacy Collaborative Learning — AI chatbots and collective efficacy in collaborative learning

Citation

Xu, H., Kharrufa, A., Solaiman, E., & Vlachokyriakos, V. (2026). AI as an Agent and Collaborative Space: Exploring the role of generative AI in small group synchronous and asynchronous collaborative dynamics. In Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI '26).