Energy Poverty Holds Back Artificial Intelligence Development Across Africa, Study Finds

Researchers Samuel Marcus, Emmanuel Uche and Onyenze Ndubueze examined the drivers of AI development across Africa between 2015 and 2023, and found that access to energy, rather than boosting technological progress, was associated with significantly weaker AI development outcomes in their model. The study, published as open access research in Discover Sustainability, took an unusual approach. Rather than asking how AI affects energy demand, as much of the existing literature does, the authors reversed the question to test how energy poverty shapes AI development.

They used panel data covering 2015 to 2023 and applied the System Generalized Method of Moments, an econometric technique designed to handle dynamic relationships in which past values of a variable influence its present trajectory. The central finding was stark: energy access significantly undermined AI development in the model the authors estimated. The work is positioned as evidence relevant to United Nations Sustainable Development Goals 7, on affordable and clean energy, and 9, on industry, innovation and infrastructure.

Not every factor the team tested behaved as expected. Globalization and human development emerged as negative and statistically insignificant determinants of AI development, a result that runs counter to the common assumption that openness to global markets and a well-educated population reliably accelerate technological uptake. The authors suggest this points to the need for a shift from general globalization toward more strategic integration policies, and for AI skill-related development programs rather than broad human capital investment alone.

Institutional quality showed a more encouraging signal. Regulatory quality exhibited marginally significant support for AI development, with a p-value of 0.057, just above the conventional 0.05 threshold. The authors interpret this as tentative evidence that effective governance and regulation can complement AI development, while cautioning that the effect falls short of standard significance levels.

The study also examined interactions between variables, and this is where some of its most practical insights emerged. The synergistic interaction between energy access and globalization policy significantly reduced the negative impact of energy access on AI development. In other words, when energy constraints were combined with globalization policy in the model, the damaging association between energy access and AI outcomes was weakened, suggesting that well-designed integration policies may partially buffer energy-related constraints.

By contrast, the interaction between energy access and regulatory quality showed a marginal negative effect on AI development that was statistically insignificant. Based on these results, the researchers recommend prioritizing affordable and reliable energy as the foundation for AI development in Africa, alongside a shift from general to strategic globalization, targeted AI skill development programs, quality institutions, effective integration policies, and broader enabling conditions. The recommendations align the findings explicitly with the sustainable development agenda, linking energy infrastructure to innovation capacity.

The study's scope and limitations are worth noting. It covers African countries over a relatively short period, 2015 to 2023, and relies on panel econometric modelling rather than experimental evidence, so the results describe statistical associations within this framework rather than proven causal effects in individual countries. The marginal significance of the regulatory quality result, and the counterintuitive findings on globalization and human development, invite further research.

Subject of Research: The relationship between energy access, globalization, human development, regulatory quality and artificial intelligence development in Africa

Article Title: Energy access, global integration, human development, and institutional complementarity for artificial intelligence development in Africa

Article References: Marcus, S., Uche, E., & Ndubueze, O. (2026). Energy access, global integration, human development, and institutional complementarity for artificial intelligence development in Africa. Discover Sustainability. https://doi.org/10.1007/s43621-026-05061-0

Image Credits: AI Generated

DOI: 10.1007/s43621-026-05061-0

Keywords: artificial intelligence, energy access, energy poverty, Africa, globalization, regulatory quality, human development, System Generalized Method of Moments, sustainable development, Discover Sustainability, Energy, access