IMF staffers cite numerous gains for Africa in using AI to grow economies

July 24, 2026 in Infrastructure, Investment, Technology & Telecoms by Editor

AI adoption in sub-Saharan Africa currently lags well behind every other region. In education, AI tutors and even simple SMS-based learning tools can support students where teachers are in short supply.

Three International Monetary Fund (IMF) staffers have said Africa does not need to win the race to build cutting-edge Artificial Intelligence (AI) models, but it must find ways to use AI widely, cheaply, and safely.

In a paper published this week, Martin Schindler, Nikola Spatafora, and Andrew Tiffin think AI can boost productivity, create better jobs, and improve public services in sub-Saharan Africa, but realizing these gains will require reliable power, affordable internet, stronger skills, and rules people trust.

Titled Africa Can Grow Faster With AI—If It Moves Now, the paper from the onset states that AI will reshape the global economy, but questions whether Africa will ride the wave or gets left behind.

It states: ‘Our research shows AI’s promise, but it also points to significant risks and challenges. At current levels of preparedness, we estimate that AI will add just 0.2 percent to the region’s GDP over the next decade—little more than a rounding error.’

‘However, if countries can put the right foundations in place to accelerate adoption and extend the impact of AI beyond today’s digitally connected firms, the gains could rise to about 4 percent over the decade—nearly half a percentage point of additional growth a year’.

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

According to the paper, this extra growth is critical given Africa’s vast jobs challenge. By 2030, sub-Saharan Africa will account for roughly half of new entrants into the global labor force. But the issue is not only the number of jobs needed—it is also their quality.

Most workers are still in informal microenterprises or smallholder agriculture, where productivity is far below that of formal firms.

For the region, AI’s main promise is not about replacing office workers, but boosting productivity across the economy—helping informal firms manage inventory, enabling farmers to increase yields, and supporting mid-sized firms to transition to formality and export readiness.

The risk is that the opposite happens. AI adoption in sub-Saharan Africa currently lags well behind every other region. If richer economies race ahead while African firms and governments lag, the productivity gap between the region and the rest of the world will only widen.

The authors go on to say the largest gains from AI may come in places people least expect. Much discussion today focuses on coders, consultants, and call centers. But, in Africa, the key question is whether AI can reach farms, schools, clinics, small businesses, and tax offices.

Agriculture is the biggest test. It employs a large share of the region’s workforce, but crop yields remain well below potential. AI tools can give farmers practical, low-cost advice—when to plant, how much fertilizer to use, how to spot pests, and how to cope with weather shocks. Kenya’s Agricultural Observatory Platform, for instance, shows how real-time weather and crop-management data can help inform farmers’ decisions.

Trials in Ghana, Nigeria, Rwanda, and Uganda suggest that digital advisories can lift yields, especially when paired with better inputs. Similar results with AI-enabled crop monitoring in South Africa shows that technology can boost yields while cutting waste.

They state: ‘The same potential extends beyond farming. In education, AI tutors and even simple SMS-based learning tools can support students where teachers are in short supply. Recent pilot programs in Nigeria show that well-designed chatbot tutoring can deliver sizable learning gains. In Rwanda, digital-skills initiatives and expanded school connectivity show how AI can support a broader skills agenda’.

In healthcare, AI will not replace Africa’s overstretched nurses and doctors, but it can help them do more by supporting triage, diagnosis, and follow-up care.

In public finance, AI-driven data analytics are already helping governments—from Kenya to South Africa—to strengthen tax compliance and mobilize revenue for development.

However, AI depends on reliable electricity, affordable broadband and data infrastructure, and workers with digital skills. That means investing in power and connectivity, supporting regional data infrastructure where viable, and strengthening digital and AI literacy through education and training.

Secondly, AI can widen inequality if its benefits are concentrated among large firms, skilled workers, and urban hubs. It also creates risks around privacy, cybersecurity, misinformation, and dependence on foreign providers.

Governments need clear and practical rules on data, competition, consumer protection, cybersecurity, and the public sector’s use of AI. Regional cooperation will also be essential. Many African economies are too small to build AI ecosystems alone. But together they can create the scale needed for infrastructure, data standards, regulation, and markets.