Africa’s artificial intelligence ambitions should begin not with the technology available to the continent, but with the problems its people need solved, a member of the United Nations-backed Independent International Scientific Panel on Artificial Intelligence has said.
Girmaw Abebe Tadesse, Principal Research Scientist and Manager at Microsoft’s AI for Good Research Lab in Kenya, says African countries risk missing the opportunity presented by artificial intelligence if they simply adopt systems designed around the priorities and realities of other regions.
Tadesse argued that African countries should first identify the challenges affecting their communities before determining the technology, infrastructure and data required to address them.
“It is important to ask ourselves what problems we want to solve first,” he said.
The argument comes as artificial intelligence moves rapidly into sectors ranging from healthcare and education to agriculture, business and public services, increasing pressure on governments to develop policies and infrastructure capable of supporting its use.
For Africa, however, the question is increasingly becoming not simply how quickly the continent can adopt AI, but whether the technology being adopted reflects African realities.
Tadesse says the starting point should be a problem-solving approach that connects AI development with challenges experienced by citizens.
Once those challenges have been identified, countries can then determine the data, infrastructure and technological systems needed to develop appropriate solutions.
This approach could shift AI conversations in Africa away from technology for its own sake and towards practical applications that respond to local needs.
It also highlights the importance of data.
AI systems depend heavily on data, yet the usefulness of those systems is closely linked to whether the data reflects the populations and environments where they are deployed. Building solutions around African realities therefore requires greater attention to locally relevant data, infrastructure and expertise.
But Tadesse says African countries cannot build this ecosystem in isolation.
He called for closer collaboration between governments, universities, development partners, technology companies and creative communities, arguing that bringing different forms of expertise together could help countries develop solutions despite limited resources.
“When we bring together diverse stakeholders, we can use existing knowledge and wisdom to produce solutions needed by our communities,” he said.
Such collaboration could also help address one of the continent’s persistent challenges: fragmented innovation.
Rather than individual countries repeatedly developing similar systems, Tadesse says African institutions should share knowledge and experiences and build on solutions that have already been developed elsewhere on the continent.
“There is a need for African countries to collaborate more, share experiences and learn from each other’s successes instead of each starting from scratch,” he said.
The need for cooperation becomes more significant as countries across Africa explore AI applications in public services, healthcare, education and agriculture.
In agriculture, for example, digital technologies are already being explored to support farmers and improve access to information. In healthcare, AI is attracting attention for its potential to support diagnosis, research and health-service delivery. Governments are also examining how emerging technologies can improve public administration.
But the scale of Africa’s AI opportunity will depend on whether such applications are designed with local conditions in mind.
Tadesse also sees Africa’s youthful population as an important part of that equation.
He said young Africans are already using technology to address problems in their communities, creating a foundation for a stronger home-grown innovation ecosystem.
The combination of young innovators, technology companies, investors and development partners, he argued, gives Africa an opportunity to become a significant centre for AI innovation focused on development.
That opportunity, however, will require more than individual innovation.
It will require countries and institutions to establish common priorities, share knowledge and build systems that can work across different African contexts.
For Tadesse, the continent does not necessarily need to reproduce the AI models developed elsewhere. Instead, it can use existing knowledge as a foundation while developing applications that respond to its own circumstances.
“If we work together, the future is bright. But we don’t have much time to wait,” he said.
As global discussions on the governance and responsible use of AI intensify, Africa’s place in that conversation is therefore becoming increasingly important.
The challenge is not only ensuring that Africans have access to AI, but ensuring that the continent has a voice in determining what the technology is built to do, whose data informs it and which problems it is expected to solve.
That could ultimately determine whether Africa remains primarily a consumer of artificial intelligence or becomes a producer of solutions shaped by its own needs.
