05 Conclusion and Recommendations
ing supporting institutional and technological in- frastructure for AI development and deployment. Therefore, due diligence is needed to account for these challenges - for example, by focusing on AI technologies that can empower rather than displace workers as well as developing schemes that focus on bridging the digital divides in Af- rican economies. Additionally, underpinning AI developments is the need for a digitally skilled workforce, as such, bridging the digital divides is vital for African countries to be better placed to benefit from advances in AI. As well as the lead- ership challenge also raises the question of what institutional development models and policies should be adopted to support AI start-ups in Af- rica. Based on the findings of this study, it was noted that the role of governments in nurturing a con- ducive innovation ecosystem environment for start-ups should be well established, to ensure
5.1 Conclusion
Africa’s Artificial intelligence landscape is evolv- ing at a rapid pace, and many countries across the continent are adopting this new way. It is no longer a Nigeria, Kenya, Tanzania, Egypt, or South Africa affair, but other less developed countries are also leveraging AI to help them solve various challenges. With continuous advancement in ma- chine learning, language processing, computer visions, and other AI subfields it is evident that indeed Africa is on the path of achieving a sus- tainable AI landscape for sustainable socioeco- nomic growth and transformation. Despite its massive potential benefits, AI is accompanied by risks and challenges, including a lack of technical skills, uncertainty, lack of structured data, lack of government policies, ethics, users’ attitudes, still faced with governance issues, and lack of institu- tional capacity which limits their ability for build-
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