AI Could Fuel Africa’s Growth Surge—If Foundations Are Laid Now

Washington — A Kenyan farmer receives planting guidance via basic mobile phone. A Nigerian teacher deploys a chatbot to help students master mathematics. South Africa’s tax authority leverages data analytics to sharpen audit targeting. These are not speculative scenarios from Silicon Valley; they are early indicators of the sweeping transformation artificial intelligence could deliver across sub-Saharan Africa.

AI is poised to rewire the global economy. The critical question for Africa is whether it harnesses this wave or watches it pass by.

Transformative Potential

New research underscores AI’s promise while flagging substantial risks. At current readiness levels, AI would contribute a mere 0.2 percent to the region’s GDP over the next decade—statistically negligible. Yet if countries establish the right foundations to accelerate adoption and extend AI’s reach beyond digitally connected firms, gains could climb to roughly 4 percent over the same period—nearly half a percentage point of additional annual growth.

That extra growth is vital given Africa’s monumental employment challenge. By 2030, sub-Saharan Africa will supply roughly half of all new entrants to the global labor force. The challenge extends beyond job quantity to quality. Most workers remain in informal microenterprises or smallholder agriculture, where productivity lags far behind formal firms.

For the region, AI’s primary promise lies not in displacing office workers but in lifting productivity economy-wide—helping informal firms manage inventory, enabling farmers to boost yields, and supporting mid-sized companies in transitioning to formality and export readiness.

The risk runs in the opposite direction. AI adoption in sub-Saharan Africa trails every other region. If advanced economies surge ahead while African firms and governments lag, the productivity gap will only widen.

A Shifted Landscape

Aid flows have always fluctuated, but the current episode is distinct. Recent cuts are large, broadly simultaneous across countries, and driven by donor decisions rather than recipient conditions. They arrive when traditional buffers are weaker: multilateral institutions and NGOs, which historically cushioned declines, face their own funding constraints. While non-traditional donors such as China and Gulf states have expanded their presence, the scale falls short of offsetting traditional donor reductions.

These cuts are harder to absorb because they follow six years of successive shocks—the pandemic, tighter global financial conditions, and food and energy crises—that have already eroded fiscal space.

Delivering on AI’s Promise

Two priorities for AI adoption stand out.

First, countries must build the foundations for broad adoption. AI depends on reliable electricity, affordable broadband, data infrastructure, and workers with digital skills. This means investing in power and connectivity, supporting regional data infrastructure where viable, and strengthening digital and AI literacy through education and training. African nations do not need to develop the world’s most powerful AI models, but they do need the capacity to adopt, adapt, and scale AI rapidly.

Second, build trust—and scale. AI can deepen inequality if benefits concentrate among large firms, skilled workers, and urban hubs. It also introduces risks around privacy, cybersecurity, misinformation, and dependence on foreign providers. Governments need clear, practical rules on data, competition, consumer protection, cybersecurity, and public-sector AI use. Regional cooperation will be essential. Many African economies are too small to build AI ecosystems alone; together they can create the scale needed for infrastructure, data standards, regulation, and markets.

AI in Africa is not merely a technology policy issue—it is central to the region’s growth strategy. Africa need not win the race to build cutting-edge models, but it must find ways to deploy AI widely, affordably, and safely. The window is narrow. Over the coming decade, Africa’s young and growing workforce will either secure more productive jobs or watch the global productivity gap widen further. The outcome will be shaped not in Silicon Valley, but in the choices made across governments, schools, farms, and firms from Dakar to Dar es Salaam.

Martin Schindler is an advisor, Nikola Spatafora is a senior economist, and Andrew Tiffin is a deputy division chief, all in the IMF’s African Department.

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