Our working paper “Artificial Intelligence and Strategic Decision-Making: Evidence from Entrepreneurs and Investors,” co-authored with Harsh Ketkar and Hyunjin Kim, is now available on SSRN.
An 18-minute video recording of my presentation about it at the wonderful Utah Strategy Summit organized by Jay Barney and Todd Zenger last week is available here.
In the same video, you can also find fascinating talks on AI by Rob Seamans, Nan Jia, and Prithwiraj Choudhury.
Our paper provides empirical evidence that current Large Language Models (LLMs) can generate and evaluate strategies at a level comparable to entrepreneurs and investors. We also propose a framework connecting AI use in strategic decision-making to firm outcomes, examining how AI impacts key cognitive processes:
- Search: How AI expands exploration of strategic alternatives
- Representation: AI’s potential to create more complex strategic models
- Aggregation: AI’s role in combining diverse strategic inputs
Key empirical findings:
- LLM-generated business plans attracted slightly higher investor interest than those by entrepreneurs admitted to a leading accelerator
- LLM evaluations of business plans are highly correlated with those of experienced investors
This framework and evidence open up exciting possibilities for how AI may reshape strategic decision-making processes and outcomes. Looking forward to further discussions on this emerging frontier!