Generative AI and collaboration: opportunities for cultivating collective intelligence

Anita Williams Woolley

Journal of Organization Design2025https://doi.org/10.1007/s41469-025-00199-zarticle
AJG 2
Weight
0.37

What the paper says

The transformative potential of artificial intelligence (AI) is reshaping collaboration within organizations, evoking both excitement and concern. As an individual production technology, AI risks fragmenting workflows, isolating workers, and undermining the human-centered collaboration vital for creativity and innovation. However, as a coordination technology, AI holds enormous promise for enhancing collective intelligence. By considering the fundamental processes underlying intelligence in any system—including reasoning, memory, and attention—we can envision ways AI can overcome traditional barriers to effective collaboration to elevate collective intelligence. This paper explores how AI can help clarify team goals and resolve conflicting motives to enhance collective reasoning; provide personalized knowledge assistance, connect complementary expertise, and mitigate biases to augment collective memory; and facilitate attention to priorities and manage asynchronous and synchronous coordination to optimize the use of collective attention. Despite these opportunities, integrating AI into collaboration presents challenges, including potential impacts on trust, cohesion, and ethical concerns. The paper outlines a research agenda to address these challenges and explore AI’s role in fostering inclusive, efficient, and innovative collaboration. By leveraging generative AI responsibly, organizations can amplify human abilities, creating synergistic outcomes that redefine the future of work.

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https://doi.org/https://doi.org/10.1007/s41469-025-00199-z

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@article{anita2025,
  title        = {{Generative AI and collaboration: opportunities for cultivating collective intelligence}},
  author       = {Anita Williams Woolley},
  journal      = {Journal of Organization Design},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1007/s41469-025-00199-z},
}

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.