In May 2024, Microsoft and Abu Dhabi-based G42 unveiled plans for a $1 billion data centre campus in Kenya powered by geothermal energy. Cassava Technologies and Nvidia have also announced plans to deploy 12,000 specialised chips across five African countries.
Meanwhile, governments from Rwanda to Nigeria are publishing national strategies that promise to turn artificial intelligence (AI) into a new engine of economic growth. There is just one problem: about half of sub-Saharan Africa still lacks reliable electricity.
Those shortfalls threaten the continent’s AI ambitions. African countries are racing to attract the infrastructure needed to power some of the world’s most advanced technology, even as millions of homes, schools, and businesses remain without dependable electricity or affordable Internet access.
The International Monetary Fund (IMF), in a report released on Tuesday, estimates that AI could increase sub-Saharan Africa’s economic output by as much as 4% over the next decade, provided countries invest in electricity, digital infrastructure, and skills. Under current conditions, the gain could be as little as 0.2%.
Martin Schindler, the IMF paper’s lead author, described the smaller figure as little more than “a rounding error”. The gap between those two scenarios is where Africa’s AI future will be decided.
While governments and workers in the United States and Europe are preoccupied with how many jobs AI might eliminate, Africa faces almost the opposite challenge: the technology may not spread widely enough to generate meaningful economic gains.
Most workers in the region are employed in agriculture, informal retail, and manual services, where today’s AI systems are less likely to replace them. But that does not make them immune. African businesses could lose customers and contracts as competitors elsewhere use AI to write software, forecast demand, manage inventory, and deliver services more efficiently.
A worker does not need to be replaced by AI to be disadvantaged by it. Their competitor only needs to become more productive.
“For sub-Saharan Africa, the central concern is not the risk of technological disruption, but whether countries will be able to adopt, adapt and scale AI quickly enough to capture its benefits and avoid falling further behind,” the IMF paper says.
That makes Africa’s AI challenge less about producing a rival to today’s leading AI models than about deploying practical tools on farms, in classrooms, in clinics, and in small businesses. It also means the continent’s place in the global AI race may ultimately depend on far less glamorous investments: transmission lines, fibre-optic networks, affordable smartphones, and workers with the skills to use the technology effectively.
Many African states are too small to build complete AI ecosystems on their own. Greater regional co-operation could allow them to share infrastructure, align regulatory frameworks, and create larger markets for AI products. Yet efforts to harmonise digital policies have often moved more slowly than the technologies they are meant to govern.
The adoption problem
Only 38% of Africans used the Internet in 2024, compared with 68% of the global population. Many more live within mobile broadband coverage yet remain offline because smartphones and mobile data are simply too expensive.
That gap between coverage and actual Internet use has become an AI gap.
A chatbot may technically be available across Africa, but availability means little to a market trader who cannot afford a smartphone, a farmer whose device cannot run the application, or a teacher who pays for every megabyte of data.
The IMF’s optimistic scenario assumes that AI will spread far beyond banks, telecom companies, large retailers, and well-funded startups. To generate meaningful economic gains, the technology will need to reach the small businesses and informal workers who account for a large share of employment across the continent.
That will require products designed around local realities rather than imported assumptions. Africa’s most consequential AI applications are likely to be standalone platforms that demand constant broadband connectivity and dollar-denominated subscriptions. Instead, they may take the form of voice assistants that understand local languages, tools embedded within WhatsApp, or systems that function reliably with low-cost devices and intermittent Internet connections.
Mobile money followed a similar path. It succeeded not by replicating Western banking’s infrastructure but by building on the mobile phones and agent networks that people already relied on.
AI will need its own version of that adaptation.
A data-centre economy
Africa has about 160 data centres, according to the IMF, with almost half concentrated in South Africa, Nigeria and Kenya. Those three markets are also attracting a significant share of the continent’s cloud computing and AI investment.
The concentration raises the prospect of a two-speed AI economy.
Businesses in Johannesburg, Lagos and Nairobi could enjoy faster and cheaper access to computing capacity. Companies in smaller or landlocked countries may continue relying on infrastructure hosted abroad, adding cost and delay.
Even countries that attract data centres are not guaranteed broad economic gains. The facilities require large capital investments but employ relatively few people once construction is complete. Their value depends on whether local startups, universities and public agencies can afford the computing power inside them.
Otherwise, Africa could end up hosting foreign-owned servers powered by African electricity while most of the commercial value is captured elsewhere.
The old problems
Governments have responded to the AI boom with strategies, task forces, and promises to train thousands of workers. These plans are necessary, particularly as the technology raises questions about privacy, cybersecurity, misinformation, and control over public data.
But a national strategy cannot compensate for a school without electricity or a government ministry whose records remain on paper.
The IMF’s findings suggest that AI policy cannot be left to technology ministries alone. Energy regulators, education departments, competition authorities and public-procurement agencies may have more influence over adoption than newly created AI councils.
African countries must also decide which part of the global race they can realistically contest. Training the largest foundation models requires billions of dollars, advanced chips, and vast amounts of electricity. Few countries on the continent can support that ambition.
A more practical strategy would focus on adapting existing models to African languages and industries, developing useful local datasets and giving researchers and businesses affordable access to computing capacity.
The valuable skill may not be creating the world’s most powerful model. It may be making an existing one work for a Kenyan farmer, a Nigerian manufacturer or a Rwandan clinic.
The IMF’s 4% estimate describes what Africa could gain. Its 0.2% estimate says more about where the continent is heading.
Africa’s AI boom is already underway in corporate offices, technology hubs, and government conference rooms. Whether it reaches the rest of the economy will depend on a more ordinary question: can people switch on a device, connect to the internet, and afford to keep using it?
For now, the answer remains uncertain.
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