Girmaw Abebe Tadesse, a member of the Independent International Scientific Panel on Artificial Intelligence and head of Microsoft’s AI for Good Lab in Kenya, said countries should identify the challenges they want to address before deciding what technology, infrastructure and data they require.
Speaking in Nairobi as global leaders and technology executives gathered at UN Headquarters in New York for High-Level Week, Tadesse argued that AI policy should begin with local needs. “We are trying to bring the reality of our environment and integrate AI technology with the local problems we face. It is important to ask ourselves what problems we want to solve first,” he said.
His intervention comes as African governments and development institutions increasingly seek to turn expanding AI investment into practical public value. A UN Development Programme assessment published this month, based on country-hosted computing deployments in Kenya, Malawi, Rwanda, South Africa, Togo and Zambia, found that hardware by itself does not create sustainable national AI capability.
UNDP said effective deployment also requires accessible data, skilled operators and users, clear institutional responsibility, cybersecurity arrangements, sustainable financing and defined routes from priority applications to working services. Across the six deployments, 21 AI applications were identified, while Rwanda separately identified 42 priority applications across eight sectors.
Tadesse said governments, universities, development partners, creative communities and technology companies should pool knowledge and expertise, particularly where resources are constrained. Such cooperation, he argued, can help ensure systems reflect local conditions rather than reproduce assumptions embedded in technologies developed for different markets and societies.
“When we bring together diverse stakeholders, we can use existing knowledge and wisdom to produce solutions needed by our communities,” he said.
The approach broadly reflects the African Union’s Continental Artificial Intelligence Strategy, which places an Africa-centred, development-focused and responsible model of AI at the heart of policy. UNDP officials have similarly argued that the key questions are which problems countries prioritise, who designs and adapts systems, what domestic capabilities are created and where the resulting economic and social value accumulates.
Local data and language representation remain central constraints. Africa has more than 2,000 languages, many with limited digital representation, complicating efforts to develop systems capable of serving populations in their own linguistic and cultural contexts. The issue has strengthened calls for locally governed datasets and models that can perform reliably beyond widely represented global languages.
Regional initiatives are also moving towards greater technological sovereignty. East African Community partner states adopted an AI declaration this year committing to a regional AI technologies fund and to systems trained on East African data, capable of supporting regional languages including Kiswahili, hosted on regional infrastructure and governed within the region.
Tadesse said Africa’s large youth population and growing technology ecosystem could become an important source of AI innovation. Young developers are already applying technology to community problems, he said, while investors and development partners have shown interest in supporting locally relevant projects.
He also cautioned against fragmented national efforts that repeatedly solve the same technical problems. African countries, he said, need stronger mechanisms to exchange experience, learn from successful projects and collaborate across borders rather than each beginning independently.
“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,” Tadesse said. “If we work together, the future is bright. But we don’t have much time to wait.”
AI applications are already spreading across education, healthcare, agriculture, business and public services, increasing pressure on governments to match experimentation with governance and operational capacity. UNDP’s work on local computing infrastructure found that progress was strongest where processing capacity was tied to usable data, appropriate skills, institutional ownership and clearly defined public-interest applications.
Follow Arabian Post
Select Arabian Post as your preferred source on Google and MSN News for trusted business news and Arab politics and updates.
