Despite notable disparities in the adoption of artificial intelligence (AI) in Africa, the drive to embrace it is most prevalent among the continent’s top economies.

Kenya, Nigeria and South Africa are some of the countries leading the way to make AI part of their economies.

This is according to global software vendor SAP, which believes AI will help to stimulate economic development on the continent, mainly in agriculture, fintech, healthcare and logistics.

“Africa is making significant progress in adopting emerging technologies, though the level of adoption varies across the continent,” said Dumisani Moyo, marketing director, SAP Africa.

“This disparity is largely driven by differences in the maturity of tech ecosystems, particularly in relation to the adoption of business AI technologies," he added.

Moyo highlighted mobile penetration and connectivity as creating a foundation for AI applications, particularly in areas like mobile banking, which has helped drive inclusion of the previously unbanked or financially excluded.

AI also has a role to play in supporting the work of government, he said. “Some African governments are implementing policies to promote AI research and development.”

“For example, in Kenya, AI has been identified as a key thematic focus by the Kenya National Innovation Agency's Strategic Plan 2023-2027; especially its application in developing innovative solutions for use in biotech, urban planning and climate change efforts.”

However, governments need to act decisively on the potential and adoption of the technology.

“For many African countries, regulatory frameworks surrounding AI are still evolving, and there are concerns about data privacy, job displacement and ethical use of AI,” Moyo stated.

International partnerships have been key in adoption, and African countries are benefiting from ties with global tech companies, which is helping to foster the growth of business AI capabilities.

However, challenges remain which are hindering adoption, said Moyo, including infrastructure limitations.

While some metropolitan regions have good connectivity, many rural areas still suffer from limited access to reliable internet, electricity and other essential infrastructure.

There are also data accessibility issues, he noted. “AI relies on large datasets, and in many African countries, data collection and management systems are either underdeveloped or fragmented.”

“Many African businesses, particularly small and medium-sized enterprises, face these challenges. However, with consumption-based models in the cloud, this is becoming less of a challenge,” he said.