Powering Development? Chinese Energy Investment, Artificial Intelligence, and Local Electrification in Africa

Access to electricity is a prerequisite for modern economic life, yet in 2023 roughly 666 million people still lived without it, 85 percent of them in Sub-Saharan Africa [1]. This paper asks whether Chinese energy investment has powered local electrification in Africa, where the pay-as-you-go (PAYG) off-grid solar model can succeed where sovereign finance has been weak, and what artificial intelligence (AI) can add to both. Linking the complete loan record of the Chinese Loans to Africa (CLA) Database - 1,319 commitments, US$180.87 billion, 2000-2024 - to World Bank access indicators for 18 Sub-Saharan countries over 2000-2023, we find no detectable country-level association between cumulative Chinese energy finance and electricity-access gains, in the cross-section (r = -0.08, p = 0.75) or in two-way fixed-effects panels. The reason is structural: the portfolio is concentrated in hydropower and extraction-linked oil finance, and in a handful of borrowers - Angola alone absorbed 41 percent of energy lending. Meanwhile, PAYG off-grid solar expanded along exactly the affordability margin the megaprojects miss: its share of affiliate off-grid sales rose from 24 to 39 percent over 2018-2023, driving 94 percent of affiliate sales growth and supplying most of the region's new connections. Finally, we show that AI attacks the information margin that both channels lack: machine learning maps the unelectrified from satellite imagery, scores repayment from mobile-phone metadata, and verifies impacts cheaply enough to make results-based finance credible - even as AI's own data centres triple their electricity demand by 2030. The future of African electrification is 'pay as you go, power as you grow', with AI as the sensing and verification layer that makes the model investable.