Towards AI as Colleagues: Multi-Agent System Improves Structured Ideation Processes
Kexin Quan, Dina Albassam, Mengke Wu, Zijian Ding, Jessie Chin
Abstract
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 processes. In a within-subjects study with 20 participants, we compared MultiColleagues to a single-agent baseline. Results show that MultiColleagues fostered stronger perceived social presence, and participants rated their outcomes as higher in quality and novelty, with more elaboration during ideation. 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.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext cfcf4b94-3515-439b-acb2-68baf4202dfaBuilds on38
- Language Models are Few-Shot LearnersTom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah et al.NeurIPS 2020 · 64,255 citations
- Training language models to follow instructions with human feedbackLong Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida et al.NeurIPS 2022 · 24,707 citations
- Measuring Massive Multitask Language UnderstandingDan Hendrycks, Collin Burns, Steven Basart, Andy Zou et al.ICLR 2021 · 7,905 citations
- CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model SocietyGuohao Li, Hasan Hammoud, Hani Itani, Dmitrii Khizbullin et al.NeurIPS 2023 · 1,975 citations
- Generative Agents: Interactive Simulacra of Human BehaviorJoon Sung Park, Joseph C. O'Brien, Carrie Jun Cai, Meredith Ringel Morris et al.UIST 2023 · 1,882 citations
Related papers
- Exploring Collaborative GenAI Agents in Synchronous Group Settings: Eliciting Team Perceptions and Design Considerations for the Future of WorkJanet G. Johnson, Macarena Peralta, Mansanjam Kaur, Ruijie Sophia Huang et al.CSCW 2025 · 16 citations
- IdeaBot: Investigating Social Facilitation in Human-Machine Team CreativityAngel Hsing-Chi Hwang, Andrea Stevenson WonCHI 2021 · 76 citations
- Multi-Agents are Social Groups: Investigating Social Influence of Multiple Agents in Human-Agent InteractionsTianqi Song, Yugin Tan, Zicheng Zhu, Yibin Feng et al.CSCW 2025 · 13 citations
- Code with Me or for Me? How Increasing AI Automation Transforms Developer WorkflowsValerie Chen, Ameet Talwalkar, Robert Brennan, Graham NeubigCHI 2026 · 2 citations
- Human-Human-AI Triadic Programming: Uncovering the Role of AI Agent and the Value of Human Partner in Collaborative LearningTaufiq Daryanto, Xiaohan Ding, Kaike Ping, Lance T. Wilhelm et al.CHI 2026 · 2 citations
