Generative Artificial Intelligence and Evaluating Strategic Decisions

40 Pages Posted: 15 Feb 2024 Last revised: 18 Feb 2024

See all articles by Anil R Doshi

Anil R Doshi

University College London - School of Management

J. Jason Bell

University of Oxford - Said Business School

Emil Mirzayev

UCL School of Management, University College London

Bart Vanneste

University College London

Date Written: February 16, 2024

Abstract

Strategic decisions involve uncertainty and are often irreversible. Hence, predicting the value of strategic alternatives is important for decision making. We investigate the potential role of generative AI in evaluating strategic alternatives. Using a sample of 60 business models, we examine the extent to which business model rankings made by large language models (LLMs) agree with those of human experts. We consider seven LLMs, ten roles for the LLM to assume, and two prompting approaches. In pairwise comparisons of business models, we find that generative AI often produces evaluations that are inconsistent and biased. However, when aggregating all evaluations, AI rankings tend to resemble those of human experts. This study highlights the value of generative AI to support strategic decision making by providing predictions.

Keywords: Generative artificial intelligence, artificial intelligence (AI), large language models (LLMs), strategic decisions, business models

Suggested Citation

Doshi, Anil Rajnikant and Bell, J. Jason and Mirzayev, Emil and Vanneste, Bart, Generative Artificial Intelligence and Evaluating Strategic Decisions (February 16, 2024). Available at SSRN: https://ssrn.com/abstract=4714776 or http://dx.doi.org/10.2139/ssrn.4714776

Anil Rajnikant Doshi

University College London - School of Management ( email )

Level 38
1 Canada Square
London, E14 5AA
United Kingdom

HOME PAGE: http://mgmt.ucl.ac.uk/

J. Jason Bell

University of Oxford - Said Business School ( email )

Park End Street
Oxford, OX1 1HP
Great Britain

Emil Mirzayev

UCL School of Management, University College London ( email )

Level 38
One Canada Square
London, E14 5AB
United Kingdom

Bart Vanneste (Contact Author)

University College London ( email )

Gower Street
London, WC1E 6BT
United Kingdom

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