Artificial Intelligence in monitoring and verifying sustainable development goal 7 progress in Africa

The review focuses on how Artificial Intelligence (AI) can transform the monitoring and verification of Sustainable Development Goal 7 (SDG 7), the goal of access to reliable, affordable, sustainable, and modern energy for all in Africa. Endowed with vast renewable resources, much of the African continent struggles with an energy access deficit, compounded by weak infrastructure, underinvestment, limited data availability, and fragmented governance. Traditional monitoring and verification approaches are typically manual, sporadic, and inadequate to ascertain dynamic change in electricity access, renewable energy adoption, and clean cooking usage. It discusses how AI techniques such as machine learning, deep learning, remote sensing integration, computer vision, and natural language processing can supply real-time, inexpensive, and scalable solutions to measure indicators of SDG 7. The paper references case studies and platforms like AtlasAI, Energy Access Explorer, and satellite-based electrification mapping tools as points of evidence on how AI can supplement ground surveys and add data granularity, predictive forecasting, and infrastructure verification. The article outlines opportunities in addition to constraints in AI adoption, touching on technical, institutional, and ethical concerns such as algorithmic bias, data privacy, lack of localized models, and narrow national capacity. The article also recognizes the importance of inclusive policy-making frameworks, open data standards, and domestic capacity development in enhancing equitable and responsible AI adoption. The review finally asserts that, with proper planning, AI can significantly catalyze the attainment of energy justice and sustainability in Africa by enabling more intelligent planning of energy, effective investments, and better governance structures.