Uncertainty-Aware Artificial Intelligence for Business Decision-Making in Africa

Artificial Intelligence (AI) is increasingly embedded in business decision-making across African economies, shaping strategic choices in finance, energy, healthcare, logistics, and digital platforms. However, most AI systems adopted in business contexts are developed under assumptions of data stability, institutional predictability, and low structural uncertainty; conditions that rarely hold in African markets. This project investigates how different forms of uncertainty (statistical, structural, contextual, and institutional) interact with AI-driven business decision-making in Africa. It develops a conceptual and analytical framework for uncertainty-aware AI, integrating insights from statistics, machine learning, and business strategy. Rather than treating uncertainty as a technical nuisance to be eliminated, the project positions uncertainty as a central feature of African business environments that must be explicitly represented, interpreted, and managed. The research is theory-led and interdisciplinary, consistent with the ethos of an Institute for Advanced Study. It focuses on conceptual synthesis, analytical frameworks, and decision-oriented interpretation rather than algorithm development or primary data collection. The project aims to contribute to African-led scholarship on responsible AI, strategic decision-making, and uncertainty in complex business systems.