Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 13

The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.

Generative AI and collaboration: opportunities for cultivating collective intelligence

Woolley, Anita Williams·2025·Journal of Organization Design

Abstract

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.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1007/s41469-025-00199-z

Cites

8 of 8 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Research works printed but not linked: 40

  1. Anderson JR, Bothell D, Byrne MD, Douglass S, Lebiere C, Qin Y (2004) An integrated theory of the mind. Psychol Rev 111(4):1036–1060 · DOI · Paper page
  2. Baddeley A (2012) Working memory: theories, models, and controversies. Annu Rev Psychol 63:1–29 · DOI · Paper page
  3. Burton JW, Lopez-Lopez E, Hechtlinger S, Rahwan Z, Aeschbach S, Bakker MA, Becker JA, Berditchevskaia A, Berger J, Brinkmann L, Flek L, Herzog SM, Huang S, Kapoor S, Narayanan A, Nussberger A-M, Yasseri T, Nickl P, Almaatouq A, Hahn U, Kurvers RHJM, Leavy S, Rahwan I, Siddarth D, Siu A, Woolley AW, Wulff DU, Hertwig R (2024) How large language models can reshape collective intelligence. Nat Hum Behav 8(9):1643–1655 · DOI
  4. Colman AM, Gold N (2018) Team reasoning: solving the puzzle of coordination. Psychon Bull Rev 25(5):1770–1783 · DOI
  5. Cronin MA, Weingart LR (2007) Representational gaps, information processing, and conflict in functionally diverse teams. Acad Manage Rev 32(3):761–773 · DOI · Paper page
  6. Crowston K, and Malone TW (1988) Information technology and work organization. Handbook of Human-Computer Interaction. https://www.sciencedirect.com/science/article/pii/B9780444705365500543 · DOI
  7. Desimone R, Duncan J (1995) Neural mechanisms of selective visual attention. Annu Rev Neurosci 18:193–222 · DOI · Paper page
  8. De Dreu CKW, Nijstad BA, van Knippenberg D (2008) Motivated information processing in group judgment and decision making. Pers Soc Psychol Rev 12(1):22–49 · DOI · Paper page
  9. Fitzsimons GM, Finkel EJ (2018) Transactive-goal-dynamics theory: a discipline-wide perspective. Curr Dir Psychol Sci 27(5):332–338 · DOI
  10. Green KC, Armstrong JS (2011) Role thinking: standing in other people’s shoes to forecast decisions in conflicts. Int J Forecast 27(1):69–80 · DOI
  11. Gupta P, Kim YJ, Glikson E, Woolley AW (2024) Using digital nudges to enhance collective intelligence in online collaboration: insights from unexpected outcomes. MIS Q 48(1):393–408 · DOI
  12. Gupta P, Nguyen TN, Gonzalez C, Woolley AW (2023) Fostering collective intelligence in human–AI collaboration: laying the groundwork for COHUMAIN. Top Cogn Sci. https://doi.org/10.1111/tops.12679 · DOI
  13. Hutchins E (1995) Cognition in the Wild. MIT Press, Cambridge · DOI · Paper page
  14. Henderson JC, Cooprider JG (1990) Dimensions of i/s planning and design aids: a functional model of CASE technology. Inf Syst Res. https://doi.org/10.1287/isre.1.3.227 · DOI
  15. Haas MR, Hansen MT (2005) When using knowledge can hurt performance: the value of organizational capabilities in a management consulting company. Strateg Manage J 26(1):1–24 · DOI · Paper page
  16. Hollnagel E, Woods DD (2005) Joint cognitive systems: foundations of cognitive systems engineering. CRC Press, Boca Raton · DOI · Paper page
  17. Johnson-Laird PN (2010) Mental models and human reasoning. Proc Natl Acad Sci U S A 107(43):18243–18250 · DOI · Paper page
  18. Jia N, Luo X, Fang Z, Liao C (2023) When and how artificial intelligence augments employee creativity. Acad Manage J. https://doi.org/10.5465/amj.2022.0426 · DOI · Paper page
  19. Lee MCM, Scheepers H, Lui AKH, Ngai EWT (2023) The implementation of artificial intelligence in organizations: a systematic literature review. Inf Manage 60(5):103816
  20. Locke EA, Shaw KN, Saari LM, Latham GP (1981) Goal setting and task performance. Psychol Bull 90(1):125–152 · DOI
  21. Mayo AT (2022) Syncing up: a process model of emergent interdependence in dynamic teams. Adm Sci Q 67(3):821–864 · DOI
  22. Newell A, Simon HA (1961) Computer simulation of human thinking: a theory of problem solving expressed as a computer program permits simulation of thinking processes. Science 134(3495):2011–2017 · DOI · Paper page
  23. Oaksford M, Chater N (2007) Bayesian rationality: the probabilistic approach to human reasoning. Oxford University Press, New York · DOI · Paper page
  24. Puranam P (2021) Human–AI collaborative decision-making as an organization design problem. J Organ des 10(2):75–80
  25. Petersen SE, Posner MI (2012) The attention system of the human brain: 20 years after. Annu Rev Neurosci 35(1):73–89 · DOI · Paper page
  26. Parent-Rocheleau X, Parker SK (2022) Algorithms as work designers: how algorithmic management influences the design of jobs. Hum Resour Manage Rev 32(3):100838
  27. Raven BH, Rietsema J (1957) The effects of varied clarity of group goal and group path upon the individual and his relation to his group. Hum Relat 10(1):29–45 · DOI
  28. Raisch S, Fomina K (2024) Combining human and artificial intelligence: hybrid problem-solving in organizations. Acad Manag Rev. https://doi.org/10.5465/amr.2021.0421 · DOI · Paper page
  29. Raveendran M, Silvestri L, Gulati R (2020) The role of interdependence in the microfoundations of organization design: task, goal, and knowledge interdependence. Acad Manag Ann. https://doi.org/10.5465/annals.2018.0015 · DOI
  30. Simon HA (1944) Decision-making and administrative organization. Public Adm Rev 4(1):16 · DOI
  31. Simon HA (1955) A behavioral model of rational choice. Q J Econ. https://doi.org/10.2307/1884852 · DOI · Paper page
  32. Squire LR (2004) Memory systems of the brain: a brief history and current perspective. Neurobiol Learn Mem 82(3):171–177 · DOI · Paper page
  33. Shin M, Kim J, van Opheusden B, Griffiths TL (2023) Superhuman artificial intelligence can improve human decision-making by increasing novelty. Proc Natl Acad Sci U S A 120(12):e2214840120 · DOI · Paper page
  34. Selenko E, Bankins S, Shoss M, Warburton J, Restubog SLD (2022) Artificial intelligence and the future of work: a functional-identity perspective. Curr Dir Psychol Sci 31(3):272–279 · DOI
  35. Schmutz JB, Outland N, Kerstan S, Georganta E, Ulfert A-S (2024) Ai-teaming: redefining collaboration in the digital era. Curr Opin Psychol 58(101837):101837 · DOI
  36. Tessler MH, Bakker MA, Jarrett D, Sheahan H, Chadwick MJ, Koster R, Evans G, Campbell-Gillingham L, Collins T, Parkes DC, Botvinick M, Summerfield C (2024) AI can help humans find common ground in democratic deliberation. Science 386(6719):eadq2852 · DOI
  37. Weingart LR (1992) Impact of group goals, task component complexity, effort, and planning on group performance. J Appl Psychol 77(5):682–693 · DOI · Paper page
  38. Woolley AW, Bear JB, Chang JW, DeCostanza AH (2013) The effects of team strategic orientation on team process and information search. Organ Behav Hum Decis Process 122(2):114–126 · DOI
  39. Woolley AW, Gupta P (2024) Understanding collective intelligence: investigating the role of collective memory, attention, and reasoning processes. Perspect Psychol Sci 19(2):344–354 · DOI
  40. Zhou X, Su Z, Feng S, Zhou J, Huang J-T, Kao H-T, Lynch S, Volkova S, Wu TS, and Woolley A. (2025) SOTOPIA-S4: a user-friendly system for flexible, customizable, and large-scale social simulation. Proceedings of the 2025 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025–06. http://maartensap.com/pdfs/zhou2025sotopiaS4.pdf · DOI

Cited by

See all 13

Metadata

Authors
Woolley, A. W.
Venue
Journal of Organization Design
Published
2025-10-10
Volume
15
Issue
1
Pages
45-50
ISSN
2245-408X
Cited by
13
References
8
Language
en
Licence
Funders
Carnegie Mellon University

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.