Fitkov-Norris, Elena and Kocheva, Nataliya (2024) Beyond the crystal ball : unveiling the power of causal and generative AI for strategic foresight. In: OR 2024 : Data, Learning, and Optimization; 3-6 Sept 2024, Munich, Germany. (Unpublished)
Abstract
This paper explores how Artificial Intelligence (AI) can revolutionize strategic foresight enhancing its capabilities and guiding decision-makers through an ever-changing landscape to navigate uncertainties through the systematic exploration of potential futures. The unparalleled pace of change encountered today necessitates robust foresight capabilities to enable businesses to navigate uncertainty. Traditional foresight techniques, while valuable, do not consider the vast quantities of available data or attempt to model complex causal relationships. The paper discusses the potential of emerging deep learning AI techniques, such as Causal and Generative AI, to enhance traditional foresight approaches by bridging the gap between quantitative and qualitative foresight methods, addressing challenges such as expert bias and data reliability. Causal AI harnesses the power of causal inference to model complex causal relationships and mitigate observational bias in data, equipping decision-makers with robust tools for scenario building. Generative AI and LLMs on the other hand, offer promising capabilities for automated horizon scanning and scenario generation, although the need for human oversight remains Ultimately, AI could empower individuals and organizations to not only anticipate the future but actively shape it.
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