- Africa Risks Missing AI Dividend Without Power, Skills and Digital Infrastructure
Artificial intelligence could become one of sub-Saharan Africa’s most powerful engines of productivity and long-term economic transformation, but the region risks capturing only a marginal share of its potential unless governments urgently invest in electricity, broadband infrastructure, digital skills and trusted regulatory systems, according to new analysis by International Monetary Fund economists.
The IMF paper warns that without decisive reforms, many sub-Saharan African economies may see productivity and growth gains of just 0.20% over the next decade from AI adoption. With stronger investment in electricity supply, internet access and digital skills, however, AI could lift the region’s economy by about 4.00% over the same period.
The contrast is striking. For a continent with the world’s youngest and fastest-growing labour force, AI can either become a productivity accelerator or another missed technological wave. The difference will not be determined by whether Africa has access to AI tools in theory, but whether firms, farmers, schools, hospitals and public institutions have the power, connectivity, data systems and skills to use them at scale.
Martin Schindler, Deputy Division Chief and Mission Chief in the IMF’s African Department and lead author of the paper, said policy changes would determine whether further growth could be unlocked from AI. Without such action, he described the projected 0.20% gain as a “rounding error”.
That warning should focus the attention of African policymakers. AI is often discussed as a futuristic threat to white-collar employment, but for sub-Saharan Africa, the more immediate risk is not mass replacement of office workers. It is exclusion from the productivity gains that richer and better-prepared economies are already positioning themselves to capture.
Sub-Saharan Africa ranks lowest on the IMF’s AI Preparedness Index, with the gap attributed to weaknesses in digital infrastructure, technical skills and regulatory capacity. The IMF paper argues that the central concern for the region is whether countries can adopt, adapt and scale AI quickly enough to benefit from it and avoid falling further behind.
This is why the AI debate in Africa must begin with electricity. Around half of the region’s population lacks reliable power, while the IMF’s April 2026 Regional Economic Outlook noted that only 53.00% of the population in sub-Saharan Africa has access to electricity and 38.00% has access to the internet. Those gaps constrain compute, digital service delivery and the spread of AI-enabled tools across the real economy.
Andrew Tiffin, one of the paper’s co-authors, put the point simply: “It’s hard to have anything without electricity.” In Africa’s case, AI has added a new layer to an old development problem. Power shortages no longer only affect factories, cold chains and households. They now also affect the ability of countries to participate meaningfully in the digital and AI economy.
Connectivity is the second binding constraint. Reuters, citing the IMF paper, reported that only 38.00% of Africans used the internet in 2024, compared with 68.00% globally. The paper argues that greater investment in fibre backbones and open-access networks could help reduce costs and expand access.
The private sector is already responding to the global AI race. Microsoft and G42 have announced a US$1.00 billion, 100-megawatt geothermal-powered data centre campus in Kenya, while Cassava Technologies and NVIDIA have struck a US$700.00 million deal to deploy 12,000 graphics processing units across South Africa, Nigeria, Kenya, Egypt and Morocco.
These investments show that Africa is not absent from the AI map. But they also reveal the risk of uneven participation. The IMF paper says Africa hosts about 160 data centres, roughly 5.50% of the global total, with nearly half located in South Africa, Nigeria and Kenya. That concentration raises the possibility that AI investment could deepen regional inequality within Africa, not just between Africa and advanced economies.
The biggest economic opportunity may lie outside the technology sector itself. For sub-Saharan Africa, AI’s most transformative uses may be in agriculture, small businesses, education, healthcare and public administration. These are the sectors where productivity is low, informality is high and service delivery gaps are most visible.
In agriculture, AI-enabled advisory tools could help farmers with weather forecasting, pest detection, crop management and market information. In education, AI-powered tutoring could support students in overcrowded classrooms and help teachers personalise learning. In healthcare, diagnostic support systems could expand access to basic medical assessment in underserved areas. In public finance, data analytics could strengthen tax compliance and reduce leakages in revenue administration.
The IMF’s April 2026 Regional Economic Outlook makes a similar point, noting that pragmatic, low-cost AI applications in revenue administration, service delivery and financial inclusion can improve productivity and state capability. But it also stresses that digitalisation must be paired with investments in energy grids, connectivity, skills, cybersecurity and data governance if countries are to build trust and scale adoption.
That makes AI a governance issue as much as a technology issue. Countries will need data protection rules, cybersecurity systems, consumer safeguards, competition frameworks and ethical standards that encourage innovation while protecting citizens. Without public trust, adoption will be slow. Without regulation, abuse and exclusion could grow. Without skills, the technology will remain imported, expensive and poorly adapted to local needs.
The IMF has urged countries to close infrastructure gaps, invest in reliable power and affordable broadband, explore regional approaches to high-performance computing, support innovation adapted to African contexts, invest in local-language datasets, and strengthen data protection and ethical frameworks.
Regional cooperation will be critical. Many African economies are too small to build full AI ecosystems alone. Shared data centres, pooled cloud procurement, harmonised digital regulations, regional digital markets and cross-border skills programmes could help countries capture economies of scale. Without such cooperation, the continent risks duplicating weak systems instead of building competitive digital infrastructure.
For Ghana and its peers, the lesson is direct. AI policy cannot sit only in ministries responsible for communications or technology. It must be integrated into energy planning, education reform, industrial policy, public-sector modernisation, tax administration and regional trade strategy.
The countries that benefit most from AI will not necessarily be those that produce the most sophisticated algorithms. They will be those that deploy AI widely into ordinary economic activity farms, clinics, classrooms, small shops, logistics networks, banks and government agencies.
Africa’s AI dividend is therefore not automatic. It must be built. It requires electricity before algorithms, broadband before platforms, skills before adoption, and governance before public trust.
The IMF’s warning is timely because the AI race is moving quickly. Advanced economies are investing heavily in data centres, chips, cloud systems and enterprise adoption. If sub-Saharan Africa waits too long, the productivity gap could widen further, making future catch-up even more difficult.
For Africa, AI is no longer a distant technology agenda. It is an economic growth imperative. The question is whether governments will treat it with the urgency required not by issuing more policy statements, but by solving the basic constraints that determine whether the continent can turn artificial intelligence into real productivity, jobs and growth.
