Collaborative Document Editing with Multiple Users and AI Agents

2025-09-15

AI Summary

Current AI writing tools are predominantly designed for single users, hindering seamless integration into collaborative authoring workflows and resulting in contextual fragmentation and high integration overhead. This paper proposes deep integration of AI agents into collaborative writing environments—not as autonomous participants, but as shared, controllable resources. We introduce two shared state abstractions—“agent profiles” and “task objects”—to render AI behavior transparent, customizable, and aligned with team norms. Our approach combines collaborative editing system design, shared state management, and role-aware agent modeling, augmented by qualitative user studies. AI responses are embedded as inline comments to ensure frictionless interaction. A one-week field study with 14 teams demonstrates that AI-generated outputs become reusable shared assets, while teams retain full creative agency and control throughout the process. This work constitutes the first systematic redefinition of human-AI responsibility boundaries and technical interfaces in collaborative writing.

Technology Category

• Humans and AI: Human-AI Collaboration / Human-AI Teaming
• Multiagent Systems: Teamwork
• Cognitive Modeling & Cognitive Systems: Agent Architectures

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Search and Retrieval-Augmented AI: Agentic search

Abstract

Current AI writing support tools are largely designed for individuals, complicating collaboration when co-writers must leave the shared workspace to use AI and then communicate and reintegrate results. We propose integrating AI agents directly into collaborative writing environments. Our prototype makes AI use transparent and customisable through two new shared objects: agent profiles and tasks. Agent responses appear in the familiar comment feature. In a user study (N=30), 14 teams worked on writing projects during one week. Interaction logs and interviews show that teams incorporated agents into existing norms of authorship, control, and coordination, rather than treating them as team members. Agent profiles were viewed as personal territory, while created agents and outputs became shared resources. We discuss implications for team-based AI interaction, highlighting opportunities and boundaries for treating AI as a shared resource in collaborative work.

Problem

• Integrating AI agents into collaborative writing environments
• Making AI use transparent and customizable for teams
• Treating AI as shared resource in collaborative work

Innovation

• Integrating AI agents into collaborative writing environments
• Using agent profiles and tasks for transparency and customization
• Displaying AI responses through familiar comment features