The developmental crevices between countries on the continent seem to be growing because of AI, but does this mean Africa will be left behind? 

The scale of the gap between Africa’s AI infrastructure and that of high-income countries (HICs) is one that continues to constrain growth and innovation. 

The rapid pace of AI innovation sits in the seat of HICs, says a 2025 World Bank report, with these countries accounting for 87% of the most well-known AI models, 86% of the startups in this space, and 91% of cumulative venture capital funding1.   

According to the African Union, more than 83% of the funding into AI startups remains in Kenya, Nigeria, South Africa and Egypt, with the continent holding only 3% of the global AI talent pool2.  

Further to this, the 2025 Government AI Readiness Index by Oxford Insights shows that only one country in Africa score higher than 50 out of 100 in AI infrastructure.  

South Africa is the highest at 55.23, followed by Mauritius (46.19), Seychelles (41.22), Botswana (40.80), and Ghana (40.60)3.  

Mark Walker, Director at T4i–a bridge between global technology capability and African market reality–believes that the divergence gap is a mix of two models. 

“AI isn’t cheap and relies on developed infrastructure which means reliable electricity, big data centers, and skilled people who run these centers and build AI on the back of them,” he says.  

“Countries like South Africa, Egypt, Kenya, Morocco and Nigeria are able to do most of that, but the rest of Africa is facing a very real challenge.” 

South Africa is much more than the seat of data centers or simply a data provider for Silicon Valley or Europe or China. The country needs to move towards a real AI foundation where models are built for Africa, by Africa, using African languages.  

This is the AI that has the potential to solve Africa’s problems because it’s relevant. “Otherwise, we are going to become the cheap labor and raw materials of AI,” Walker adds.  

AI innovation established in Africa also makes sense from a geopolitical perspective. Iginio Gagliardone, Professor: Department of Media Studies at the University of the Witwatersrand, believes that in an environment of increased polarization between the United States and China, the continent is one of the few places that can accommodate data centers from Alibaba, Huawei, Amazon, and Microsoft.  

“Here, engineers from different countries across Africa are developing a unique set of skills that are able to integrate tools in meaningful and effective ways,” he says.  

“Technology comes from multiple sources–Huawei, IBM, [countries like] Australia, China–and local engineers can work across multiple systems. This is a unique skillset in Africa and should be leveraged.” 

The ability to make sense of, connect and integrate different innovations that come from different places has the potential to place the continent, firmly, in the center of AI change, and to mitigate the risk of the gap widening.  

However, this does mean challenging current convention and moving Africa away from its reliance on external AI organizations while reframing the conversations around data sovereignty. 

“The data is owned by the companies that host them and this is causing conflict everywhere, even Europe is trying to flex its muscles in this regard,” says Gagliardone.  

“The CLOUD Act in the United States is also a concern–companies headquartered in the United States are forced to share the data stored by them, without a court injunction, even when that data is stored outside the United States. This challenges data sovereignty.” 

Data is, of course, a commodity. It allows companies to sharpen their services, gain momentum and build for need. It is also primarily owned by companies that do not sit in Africa.  

There isn’t a South African or Nigerian version of ChatGPT or Facebook or Instagram, but as these tools evolve and arrive, countries also need to be able to do something with the data they create. The continent needs the ecosystem and infrastructure that would allow it to make meaningful use of the data.  

“Essentially, AI isn’t creating inequalities from ground zero, it is widening gaps in some areas while exposing some structural disparities,” says Ravi Bhat, Chief Solutions and AI Transformation Officer at Microsoft Africa.  

“The question is, what do we need to do to reduce the gap and not create more inequalities. We need to focus on data quality, digital infrastructure, and skills while making adoption of AI easier.” 

And, as Walker points out, it’s just as important to recognize how well Africa is doing in the AI space. 

“Kenya and Egypt are doing some amazing work. What we need to figure out is how we can harness this work,” he says.  

“A digital marketplace that provides AI solutions that deal with AI-specific problems? An ecosystem that allows funds to flow back into employment and skills development? We need to think of ways to step into AI and move it from extraction to empowerment, so Africa isn’t just consuming Western models and tools.” 

It’s time to ask difficult questions and find ways of bringing AI into the center of Africa’s innovation ecosystems. What toolboxes can be used? What steps need to be taken? And how can African countries learn from others, to ensure they are not left behind?