IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2405.17924.html
   My bibliography  Save this paper

Generative AI Enhances Team Performance and Reduces Need for Traditional Teams

Author

Listed:
  • Ning Li
  • Huaikang Zhou
  • Kris Mikel-Hong

Abstract

Recent advancements in generative artificial intelligence (AI) have transformed collaborative work processes, yet the impact on team performance remains underexplored. Here we examine the role of generative AI in enhancing or replacing traditional team dynamics using a randomized controlled experiment with 435 participants across 122 teams. We show that teams augmented with generative AI significantly outperformed those relying solely on human collaboration across various performance measures. Interestingly, teams with multiple AIs did not exhibit further gains, indicating diminishing returns with increased AI integration. Our analysis suggests that centralized AI usage by a few team members is more effective than distributed engagement. Additionally, individual-AI pairs matched the performance of conventional teams, suggesting a reduced need for traditional team structures in some contexts. However, despite this capability, individual-AI pairs still fell short of the performance levels achieved by AI-assisted teams. These findings underscore that while generative AI can replace some traditional team functions, more comprehensively integrating AI within team structures provides superior benefits, enhancing overall effectiveness beyond individual efforts.

Suggested Citation

  • Ning Li & Huaikang Zhou & Kris Mikel-Hong, 2024. "Generative AI Enhances Team Performance and Reduces Need for Traditional Teams," Papers 2405.17924, arXiv.org.
  • Handle: RePEc:arx:papers:2405.17924
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2405.17924
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lingfei Wu & Dashun Wang & James A. Evans, 2019. "Large teams develop and small teams disrupt science and technology," Nature, Nature, vol. 566(7744), pages 378-382, February.
    2. Rachit Dubey & Mathew D. Hardy & Thomas L. Griffiths & Rahul Bhui, 2024. "AI-generated visuals of car-free US cities help improve support for sustainable policies," Nature Sustainability, Nature, vol. 7(4), pages 399-403, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gao, Qiang & Liang, Zhentao & Wang, Ping & Hou, Jingrui & Chen, Xiuxiu & Liu, Manman, 2021. "Potential index: Revealing the future impact of research topics based on current knowledge networks," Journal of Informetrics, Elsevier, vol. 15(3).
    2. Wenxuan Shi & Renli Wu, 2024. "Women’s strength in science: exploring the influence of female participation on research impact and innovation," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(7), pages 4529-4551, July.
    3. Hoekman, Jarno & Rake, Bastian, 2024. "Geography of authorship: How geography shapes authorship attribution in big team science," Research Policy, Elsevier, vol. 53(2).
    4. Guoqiang Liang & Ying Lou & Haiyan Hou, 2022. "Revisiting the disruptive index: evidence from the Nobel Prize-winning articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(10), pages 5721-5730, October.
    5. Yu, Shuo & Alqahtani, Fayez & Tolba, Amr & Lee, Ivan & Jia, Tao & Xia, Feng, 2022. "Collaborative Team Recognition: A Core Plus Extension Structure," Journal of Informetrics, Elsevier, vol. 16(4).
    6. Gallus, Jana & Bhatia, Sudeep, 2020. "Gender, power and emotions in the collaborative production of knowledge: A large-scale analysis of Wikipedia editor conversations," Organizational Behavior and Human Decision Processes, Elsevier, vol. 160(C), pages 115-130.
    7. Peter Sjögårde & Fereshteh Didegah, 2022. "The association between topic growth and citation impact of research publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(4), pages 1903-1921, April.
    8. Shuo Xu & Liyuan Hao & Xin An & Hongshen Pang & Ting Li, 2020. "Review on emerging research topics with key-route main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 607-624, January.
    9. Michele Pezzoni & Fabiana Visentin, 2024. "Gender bias in team formation: the case of the European Science Foundation’s grants," Science and Public Policy, Oxford University Press, vol. 51(2), pages 247-260.
    10. You, Taekho & Park, Jinseo & Lee, June Young & Yun, Jinhyuk & Jung, Woo-Sung, 2022. "Disturbance of questionable publishing to academia," Journal of Informetrics, Elsevier, vol. 16(2).
    11. Cinzia Daraio & Simone Di Leo & Loet Leydesdorff, 2022. "Using the Leiden Rankings as a Heuristics: Evidence from Italian universities in the European landscape," LEM Papers Series 2022/08, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    12. Wu, Lingfei & Kittur, Aniket & Youn, Hyejin & Milojević, Staša & Leahey, Erin & Fiore, Stephen M. & Ahn, Yong-Yeol, 2022. "Metrics and mechanisms: Measuring the unmeasurable in the science of science," Journal of Informetrics, Elsevier, vol. 16(2).
    13. Pierre Azoulay & Danielle Li, 2020. "Scientific Grant Funding," NBER Working Papers 26889, National Bureau of Economic Research, Inc.
    14. Li, Heyang & Wu, Meijun & Wang, Yougui & Zeng, An, 2022. "Bibliographic coupling networks reveal the advantage of diversification in scientific projects," Journal of Informetrics, Elsevier, vol. 16(3).
    15. Bellis, Paola & Cunial, Matteo & Trabucchi, Daniel, 2024. "Mastering hybrid worlds through digital leadership: The role of agility in fostering innovation," Business Horizons, Elsevier, vol. 67(4), pages 369-380.
    16. Sam Arts & Nicola Melluso & Reinhilde Veugelers, 2023. "Beyond Citations: Measuring Novel Scientific Ideas and their Impact in Publication Text," Papers 2309.16437, arXiv.org, revised Oct 2024.
    17. K. Brad Wray & Søren R. Paludan & Lutz Bornmann & Robin Haunschild, 2024. "Using Reference Publication Year Spectroscopy (RPYS) to analyze the research and publication culture in immunology," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(6), pages 3271-3283, June.
    18. Zhentao Liang & Jin Mao & Gang Li, 2023. "Bias against scientific novelty: A prepublication perspective," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(1), pages 99-114, January.
    19. Yue Wang & Ning Li & Bin Zhang & Qian Huang & Jian Wu & Yang Wang, 2023. "The effect of structural holes on producing novel and disruptive research in physics," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1801-1823, March.
    20. Pan Zhang & Yongjun Du & Sijie Han & Qingan Qiu, 2022. "Global Progress in Oil and Gas Well Research Using Bibliometric Analysis Based on VOSviewer and CiteSpace," Energies, MDPI, vol. 15(15), pages 1-27, July.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2405.17924. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.