Businesses are increasingly using strategic foresight methodologies like scenario planning to anticipate and address the escalating organizational uncertainties driven by climate change, global conflicts, and rapid technological advancements. However, traditional approaches to scenario planning have some inherent shortcomings. They include inadequacies in identifying the most relevant trends and external forces, based on varied levels of uncertainty; limits on how many scenarios they can consider in depth; and the lack of direction they provide for how to assess and prepare for multiple highly divergent scenarios simultaneously.
A promising alternative is emerging that can overcome these challenges. It entails enlisting the assistance of cutting-edge generative AI powered by large neural network models such as OpenAI’s GPT and Anthropic’s Claude. They can significantly enhance an organization’s capability to conduct robust contingency scenario planning faster and at a much lower cost than conventional processes. This approach is particularly beneficial for resource-constrained organizations like small and medium-sized enterprises (SMEs) that are operating in highly challenging environments, such as those prone to extreme weather events.
In addressing this topic, we have leveraged our diverse experiences studying and conducting experiments using generative AI for strategic planning in academic, commercial, and government contexts, and advising organizations on contingency strategies in multiple domains, including supply chains, defense, and pandemic response. Our conversations with chief experience officers (CXOs) at over 10 companies and recent feedback gathered from a large conference of chief procurement officers (CPOs) in the United States indicate that many organizations, including Fortune 500 firms, are actively exploring the use of generative AI for strategic foresight, including scenario planning.
