Africa Needs Its Own AI Solutions, Not Borrowed Ones

Africa’s AI debate is moving from whether the continent will adopt artificial intelligence to a more important question: who will define the problems the technology is built to solve?

Girmaw Abebe Tadesse of Microsoft’s AI for Good Lab in Kenya has argued that African countries need locally grounded AI solutions rather than systems copied from other markets. The argument is not a rejection of global technology. It is a reminder that tools designed elsewhere may not understand African languages, institutions, data constraints or social priorities.

Starting with local problems changes the order of work. Instead of choosing a model first and searching for a use case later, governments, researchers and companies can begin with needs in health, agriculture, education, public administration and climate resilience. They can then decide what data, infrastructure and skills are required to address those needs responsibly.

That approach also puts young people and local institutions at the centre of deployment. African AI ecosystems need engineers and researchers, but they also need domain experts, public servants and communities able to test whether a system is useful in practice.

The strategic risk is dependency. Countries that only import AI products may gain short-term access while remaining dependent on external platforms, pricing decisions and data practices. Countries that build capabilities locally have more room to adapt, question and govern what they use.

The shift will take time. Capability depends on education, compute, public datasets, procurement and patient funding. But the principle is clear: Africa’s AI future will be stronger when local priorities shape the technology, rather than appearing as an afterthought.

Source: Global Issues, republishing UN News coverage.