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Measuring Human Leadership Skills with Artificially Intelligent Agents

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  • Ben Weidmann
  • Yixian Xu
  • David J. Deming

Abstract

We show that the ability to lead groups of humans is predicted by leadership skill with Artificially Intelligent agents. In a large pre-registered lab experiment, human leaders worked with AI agents to solve problems. Their performance on this 'AI leadership test' was strongly correlated with their causal impact on human teams, which we estimate by repeatedly randomly assigning leaders to groups of human followers and measuring team performance. Successful leaders of both humans and AI agents ask more questions and engage in more conversational turn-taking; they score higher on measures of social intelligence, fluid intelligence, and decision-making skill, but do not differ in gender, age, ethnicity or education. Our findings indicate that AI agents can be effective proxies for human participants in social experiments, which greatly simplifies the measurement of leadership and teamwork skills.

Suggested Citation

  • Ben Weidmann & Yixian Xu & David J. Deming, 2025. "Measuring Human Leadership Skills with Artificially Intelligent Agents," Papers 2508.02966, arXiv.org.
    • Handle: RePEc:arx:papers:2508.02966
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    References listed on IDEAS

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    1. Jason W. Burton & Ezequiel Lopez-Lopez & Shahar Hechtlinger & Zoe Rahwan & Samuel Aeschbach & Michiel A. Bakker & Joshua A. Becker & Aleks Berditchevskaia & Julian Berger & Levin Brinkmann & Lucie Fle, 2024. "How large language models can reshape collective intelligence," Nature Human Behaviour, Nature, vol. 8(9), pages 1643-1655, September.
    2. David J. Deming, 2017. "The Growing Importance of Social Skills in the Labor Market," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(4), pages 1593-1640.
    3. Argyle, Lisa P. & Busby, Ethan C. & Fulda, Nancy & Gubler, Joshua R. & Rytting, Christopher & Wingate, David, 2023. "Out of One, Many: Using Language Models to Simulate Human Samples," Political Analysis, Cambridge University Press, vol. 31(3), pages 337-351, July.
    4. Milena Tsvetkova & Taha Yasseri & Niccolo Pescetelli & Tobias Werner, 2024. "A new sociology of humans and machines," Nature Human Behaviour, Nature, vol. 8(10), pages 1864-1876, October.
    5. John J. Horton, 2023. "Large Language Models as Simulated Economic Agents: What Can We Learn from Homo Silicus?," NBER Working Papers 31122, National Bureau of Economic Research, Inc.
    6. John J. Horton, 2023. "Large Language Models as Simulated Economic Agents: What Can We Learn from Homo Silicus?," Papers 2301.07543, arXiv.org.
    7. Ben Weidmann & David J. Deming, 2021. "Team Players: How Social Skills Improve Team Performance," Econometrica, Econometric Society, vol. 89(6), pages 2637-2657, November.
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