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Artificial Intelligence and Strategic Decision-Making: Evidence from Entrepreneurs and Investors

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  • Felipe A. Csaszar
  • Harsh Ketkar
  • Hyunjin Kim

Abstract

This paper explores how artificial intelligence (AI) may impact the strategic decision-making (SDM) process in firms. We illustrate how AI could augment existing SDM tools and provide empirical evidence from a leading accelerator program and a startup competition that current Large Language Models (LLMs) can generate and evaluate strategies at a level comparable to entrepreneurs and investors. We then examine implications for key cognitive processes underlying SDM -- search, representation, and aggregation. Our analysis suggests AI has the potential to enhance the speed, quality, and scale of strategic analysis, while also enabling new approaches like virtual strategy simulations. However, the ultimate impact on firm performance will depend on competitive dynamics as AI capabilities progress. We propose a framework connecting AI use in SDM to firm outcomes and discuss how AI may reshape sources of competitive advantage. We conclude by considering how AI could both support and challenge core tenets of the theory-based view of strategy. Overall, our work maps out an emerging research frontier at the intersection of AI and strategy.

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  • Felipe A. Csaszar & Harsh Ketkar & Hyunjin Kim, 2024. "Artificial Intelligence and Strategic Decision-Making: Evidence from Entrepreneurs and Investors," Papers 2408.08811, arXiv.org.
    • Handle: RePEc:arx:papers:2408.08811
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    1. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 69(1), pages 99-118.
    2. Jens Ludwig & Sendhil Mullainathan, 2024. "Machine Learning as a Tool for Hypothesis Generation," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 139(2), pages 751-827.
    3. Mary Tripsas & Giovanni Gavetti, 2000. "Capabilities, cognition, and inertia: evidence from digital imaging," Strategic Management Journal, Wiley Blackwell, vol. 21(10‐11), pages 1147-1161, October.
    4. Nicholas Bloom & Raffaella Sadun, 2012. "The Organization of Firms Across Countries," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 127(4), pages 1663-1705.
    5. Prithwiraj Choudhury & Dan Wang & Natalie A. Carlson & Tarun Khanna, 2019. "Machine learning approaches to facial and text analysis: Discovering CEO oral communication styles," Strategic Management Journal, Wiley Blackwell, vol. 40(11), pages 1705-1732, November.
    6. Erik Brynjolfsson & Wang Jin & Kristina McElheran, 2021. "The power of prediction: predictive analytics, workplace complements, and business performance," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 56(4), pages 217-239, October.
    7. Benjamin S. Manning & Kehang Zhu & John J. Horton, 2024. "Automated Social Science: Language Models as Scientist and Subjects," Papers 2404.11794, arXiv.org, revised Apr 2024.
    8. Felipe A. Csaszar & J. P. Eggers, 2013. "Organizational Decision Making: An Information Aggregation View," Management Science, INFORMS, vol. 59(10), pages 2257-2277, October.
    9. Yash Raj Shrestha & Vivianna Fang He & Phanish Puranam & Georg von Krogh, 2021. "Algorithm Supported Induction for Building Theory: How Can We Use Prediction Models to Theorize?," Organization Science, INFORMS, vol. 32(3), pages 856-880, May.
    10. Shai Bernstein & Arthur Korteweg & Kevin Laws, 2017. "Attracting Early-Stage Investors: Evidence from a Randomized Field Experiment," Journal of Finance, American Finance Association, vol. 72(2), pages 509-538, April.
    11. Alberto Abadie & Susan Athey & Guido W Imbens & Jeffrey M Wooldridge, 2023. "When Should You Adjust Standard Errors for Clustering?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 138(1), pages 1-35.
    12. Felipe A. Csaszar, 2018. "What Makes a Decision Strategic? Strategic Representations," Strategy Science, INFORMS, vol. 3(4), pages 606-619, December.
    13. Felipe A. Csaszar, 2012. "Organizational structure as a determinant of performance: Evidence from mutual funds," Strategic Management Journal, Wiley Blackwell, vol. 33(6), pages 611-632, June.
    14. Timo Ehrig & Jens Schmidt, 2022. "Theory‐based learning and experimentation: How strategists can systematically generate knowledge at the edge between the known and the unknown," Strategic Management Journal, Wiley Blackwell, vol. 43(7), pages 1287-1318, July.
    15. 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.
    16. Sarah Kaplan, 2011. "Strategy and PowerPoint: An Inquiry into the Epistemic Culture and Machinery of Strategy Making," Organization Science, INFORMS, vol. 22(2), pages 320-346, April.
    17. Deborah Dougherty, 1992. "Interpretive Barriers to Successful Product Innovation in Large Firms," Organization Science, INFORMS, vol. 3(2), pages 179-202, May.
    18. John J. Horton, 2023. "Large Language Models as Simulated Economic Agents: What Can We Learn from Homo Silicus?," Papers 2301.07543, arXiv.org.
    19. Felipe A. Csaszar & Daniella Laureiro-Martínez, 2018. "Individual and Organizational Antecedents of Strategic Foresight: A Representational Approach," Strategy Science, INFORMS, vol. 3(3), pages 513-532, September.
    20. Daniel A. Levinthal, 1997. "Adaptation on Rugged Landscapes," Management Science, INFORMS, vol. 43(7), pages 934-950, July.
    21. Jiankun Sun & Dennis J. Zhang & Haoyuan Hu & Jan A. Van Mieghem, 2022. "Predicting Human Discretion to Adjust Algorithmic Prescription: A Large-Scale Field Experiment in Warehouse Operations," Management Science, INFORMS, vol. 68(2), pages 846-865, February.
    22. Rembrand Koning & Sharique Hasan & Aaron Chatterji, 2022. "Experimentation and Start-up Performance: Evidence from A/B Testing," Management Science, INFORMS, vol. 68(9), pages 6434-6453, September.
    23. Arnaldo Camuffo & Alessandro Cordova & Alfonso Gambardella & Chiara Spina, 2020. "A Scientific Approach to Entrepreneurial Decision Making: Evidence from a Randomized Control Trial," Management Science, INFORMS, vol. 66(2), pages 564-586, February.
    24. Benjamin S. Manning & Kehang Zhu & John J. Horton, 2024. "Automated Social Science: Language Models as Scientist and Subjects," NBER Working Papers 32381, National Bureau of Economic Research, Inc.
    25. Felipe A. Csaszar & Daniel A. Levinthal, 2016. "Mental representation and the discovery of new strategies," Strategic Management Journal, Wiley Blackwell, vol. 37(10), pages 2031-2049, October.
    26. Dongil D. Keum & Kelly E. See, 2017. "The Influence of Hierarchy on Idea Generation and Selection in the Innovation Process," Organization Science, INFORMS, vol. 28(4), pages 653-669, August.
    27. Dirk Martignoni & Anoop Menon & Nicolaj Siggelkow, 2016. "Consequences of misspecified mental models: Contrasting effects and the role of cognitive fit," Strategic Management Journal, Wiley Blackwell, vol. 37(13), pages 2545-2568, December.
    28. Sofia Bapna, 2019. "Complementarity of Signals in Early-Stage Equity Investment Decisions: Evidence from a Randomized Field Experiment," Management Science, INFORMS, vol. 65(2), pages 933-952, February.
    29. Bo Cowgill, 2019. "Bias and Productivity in Humans and Machines," Upjohn Working Papers 19-309, W.E. Upjohn Institute for Employment Research.
    30. Paul R. Carlile, 2002. "A Pragmatic View of Knowledge and Boundaries: Boundary Objects in New Product Development," Organization Science, INFORMS, vol. 13(4), pages 442-455, August.
    31. Giovanni Gavetti & Anoop Menon, 2016. "Evolution Cum Agency: Toward a Model of Strategic Foresight," Strategy Science, INFORMS, vol. 1(3), pages 207-233, September.
    32. Teppo Felin & Todd R. Zenger, 2017. "The Theory-Based View: Economic Actors as Theorists," Strategy Science, INFORMS, vol. 2(4), pages 258-271, December.
    33. Teppo Felin & Stuart Kauffman & Roger Koppl & Giuseppe Longo, 2014. "Economic Opportunity and Evolution: Beyond Landscapes and Bounded Rationality," Post-Print hal-01415115, HAL.
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