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Real test lies ahead for Kenya’s new AI roadmap
We must treat AI the same way, nurture it with trust and regulate it with wisdom.
Kenya has published an implementation roadmap for the previously launched Artificial Intelligence (AI) Strategy that sets out how the government wants the technology embedded across public services and key economic sectors by 2030. This is even as it identifies power generation, skills, data and trust as key pillars of success.
The strategy implementation roadmap 2025–2030, developed under the Ministry of ICT and the Digital Economy, positions AI as a “cross-cutting enabler” of national transformation and ties the plan to existing national frameworks, including the Digital Economy Blueprint, Vision 2030 and the Bottom-Up Economic Transformation Agenda.
The draft roadmap promises to make AI the practical anchor of smarter public services, new tools for farmers and clinics, faster decisions in finance and government, under clearer rules meant to prevent abuse, bias and exclusion.
It is organised around five pillars, including advanced digital infrastructure, secure national datasets and locally relevant large language models, and high-impact applications in priority sectors. The roadmap also seeks to build a sustainable AI innovation ecosystem anchored in agile governance and ethical oversight.
The document uses a simple constraint to rally public support for the project, warning that “you cannot run the future on weak foundations.” The plan treats infrastructure as the make-or-break layer, pointing to AI-ready data centres, national computing platforms, expanded fibre, Internet Protocol Version 6 (IPv6) networks and 5G-enabled services as foundational requirements.
Network slicing
The infrastructure section not only covers AI data centres and optical networks but also wireless networks, emphasising them as key for individual and industrial users to be able to use AI. In wireless networks, it calls for greater use of AI in optimisation, more edge computing and the use of network slicing for specific use cases and an ambitious national target of 80 per cent 5G population coverage by 2030. This ties in faster and wider connectivity to next-generation use cases such as real-time analytics and advanced industrial applications.
It recognises the importance of low latency networks for individuals to take advantage of AI in developing content and then, more critically, for industrial users, who will leverage AI in automation. This makes sense for AI-driven automation that, though not widely developed in Kenya now, could be implemented more broadly across industries in the future.
That target lands in a market where key operators are still building momentum. Safaricom, for instance, has been expanding its 5G network across the 47 counties, but the scale of investment required to reach the 80 per cent population coverage threshold by 2030 underscores what remains to be built, including transmission, last-mile connectivity and the energy reliability needed to keep networks and data centres running.
The roadmap prioritises secure national datasets and the development of locally relevant AI models, including Swahili-language systems, a nod to a reality too often ignored in imported technology.
The draft arrives in a world where AI is moving faster than institutions. Kenya’s standing in the Government AI Readiness Index has been cited as closed in governance, skills and infrastructure if policies are to translate into services people can feel around governance and ethics.
Public interest
The roadmap calls for oversight through a strong legal framework, cultural values and public interest — an implicit acknowledgement of the citizens’ fear that AI is leading them to a future where decisions are automated without accountability.
Kenya seeks to deploy AI tools in key sectors of the economy, including agriculture, where such tools could help predict pest infestation, optimise fertiliser use and reduce post-harvest losses. In health, AI will assist with pre-screening and diagnosis using quality data and protected privacy. In education, AI can personalise learning within solid guardrails to minimise cheating, misinformation and new forms of exclusion. The roadmap lists agriculture, healthcare, education, tourism, financial services and digital government as early priorities for deployment.
The draft also gestures outwards, drawing lessons from global AI leaders and fast movers globally. It concludes that successful mainstreaming of AI requires investment, training and regulation all at once, even as it warns that Kenya’s roadmap will rise or fall on whether it can sustain funding beyond political cycles, build advanced skills at scale, and keep regulation firm enough to protect citizens and flexible enough to support innovation.
Mr Kiprono is a media consultant on technology issues
