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Towards AI as Colleagues: Multi-Agent System Improves Structured Professional Ideation

Published: October 27, 2025 | arXiv ID: 2510.23904v1

By: Kexin Quan , Dina Albassam , Mengke Wu and more

Potential Business Impact:

AI agents brainstorm better ideas with people.

Business Areas:
Artificial Intelligence Artificial Intelligence, Data and Analytics, Science and Engineering, Software

Most AI systems today are designed to manage tasks and execute predefined steps. This makes them effective for process coordination but limited in their ability to engage in joint problem-solving with humans or contribute new ideas. We introduce MultiColleagues, a multi-agent conversational system that shows how AI agents can act as colleagues by conversing with each other, sharing new ideas, and actively involving users in collaborative ideation. In a within-subjects study with 20 participants, we compared MultiColleagues to a single-agent baseline. Results show that MultiColleagues fostered stronger perceptions of social presence, produced ideas rated significantly higher in quality and novelty, and encouraged deeper elaboration. These findings demonstrate the potential of AI agents to move beyond process partners toward colleagues that share intent, strengthen group dynamics, and collaborate with humans to advance ideas.

Country of Origin
🇺🇸 United States

Page Count
36 pages

Category
Computer Science:
Human-Computer Interaction