Kenya has been placed fifth in Africa on AI preparedness in new global rankings by the World Trade Organisation (WTO). The WTO assessment positions Kenya behind Seychelles, Mauritius, South Africa, and Tunisia, while placing the country 77th globally out of 132 nations assessed.
The ranking adds to a growing body of international assessments that increasingly place Kenya among Africa’s upper tier on emerging technology preparedness, even as structural gaps continue to constrain full-scale AI deployment.
While the WTO methodology was not disclosed in detail, AI preparedness rankings typically assess digital infrastructure, skills availability, data governance, regulatory frameworks, and the capacity to integrate AI into economic activity.
Kenya’s position reflects years of investment in digital public infrastructure, mobile connectivity, and a technology-led services economy that has made Nairobi a regional innovation hub.
Kenya has previously performed strongly in similar assessments, including a 2022 government AI readiness index by Oxford Insights, where Kenya also ranked fifth in Africa.
In the earlier ranking, Kenya trailed Egypt, South Africa, Tunisia, and Morocco, and was placed 90th globally, highlighting progress in relative global positioning since then.
However, the 2022 index flagged deep weaknesses in technology skills, with Kenya scoring below the global average on the availability of specialised talent needed for AI adoption.
The new WTO ranking comes as Kenya begins implementing its national AI strategy for the 2025–2030, which outlines priority sectors and foundational reforms. Under the strategy, healthcare, education, and agriculture have been identified as the first focus areas for AI deployment, reflecting sectors where efficiency gains could deliver broad social impact.
In healthcare, proposed use cases include maternal health chatbots in local languages and disease advisory systems designed to improve access to accurate medical information.
Education priorities include intelligent tutoring systems and multilingual teacher training tools aimed at improving learning outcomes and expanding access to quality instruction.
In agriculture, the strategy highlights AI-powered fertiliser recommendations and translation of complex data into farmer-friendly audio formats in local dialects.
Beyond sector applications, the strategy further identifies three core pillars for AI uptake, including modernising digital infrastructure, building a national data ecosystem, and incentivising local AI model development.
The government has acknowledged widespread concern over the absence of a dedicated AI legal framework, particularly as private-sector adoption accelerates faster than regulation.
Authorities argue that existing laws, including the Data Protection Act and the Computer Misuse and Cybercrimes Act, provide an initial governance foundation for AI deployment.
