Kenya is positioning itself as a continental leader in artificial intelligence by operationalising its Cloud‑First Policy and building robust data infrastructure.
The ongoing pre-consolidation briefing sessions on AI and emerging technologies policy roundtable discussions with the government, private sector and tech community on Wednesday revealed a pragmatic approach: treat cloud and data as public goods, unlock sharing frameworks, and design regulation that attracts capital while safeguarding citizens.
The policy development process is being led by the Ministry of Information, Communication and the Digital Economy (MICDE), with KICTANet serving as the primary implementing partner. It is supported by the British High Commission (BHC) in Nairobi through its governance and digital transformation portfolio. This collaboration forms part of the broader UK–Kenya strategic partnership on responsible AI and emerging technologies, underscoring the UK’s commitment to advancing ethical, inclusive, and transparent AI governance frameworks across Africa.
Cloud‑First Policy Moves Into Action
Kenya’s Cloud‑First Policy has moved beyond drafting and is now officially approved and in use. A government representative confirmed:
“The Cloud First policy is approved and in use, and what we have just done… is to come up with [guidelines] which are also finalized. So the guidelines will also be operational once they [are] approved in the next month or so. So that one, we are one of the first countries in the continent to have that,” disclosed Director Partnerships Research and Emerging Technologies, John Kiria.
The upcoming guidelines will clarify how government agencies consume cloud services, outline security and compliance expectations, and define the role of local versus foreign providers.
Kenya already hosts three or four of Africa’s nine or ten tier‑three data centres, a strategic advantage that requires deliberate policy alignment to fully leverage.
“Kenya is the only country, I think, out of nine or 10 tier three data centers, three or four in Kenya [in the] African continent. That’s impressive, but we still need to be very intentional in terms of how we’re thinking about that infrastructure and the policy.”
Data as Infrastructure: Government Must “Build the Roads”
A recurring metaphor captured the urgency: data is the new infrastructure, and government must act as the road‑builder.
“It’s almost like… the government needs to actually build the roads so that the Kenyan citizens can then build, and there is no possibility for real estate in a place that is completely inaccessible. And this is why the ‘data as infrastructure’ approach really, really makes sense… for Kenya and the Kenyan government.”
Without foundational public datasets, especially in health, startups are forced to spend scarce capital on acquiring or cleaning data, making scaling nearly impossible.
“Every single startup will have its own data set… It’s impossible. We cannot scale if we are thinking like that.”
National Data Management and Sharing Policy
Kenya is racing to complete a national data management policy to define how data is categorized, shared, and governed across the public sector.
“In terms of data sharing, the data management policy is ongoing… it will cover all… aspects of data, sharing, anything to do with the data, it will be covered under that policy.”
Stakeholders flagged grey areas around ownership and access, urging government to provide clear guidelines. This effort ties directly into Kenya’s broader digital public infrastructure (DPI) agenda, treating public data assets as shared national infrastructure with privacy and security safeguards.
Regulation as a Magnet for Investment
Despite global AI investment exceeding USD 200 billion last year, Africa captured only a fraction. Kenya’s experts argue that regulatory clarity is the missing magnet for capital.
“Last year, over 200 billion US dollars were funded in the AI space. But if you look [at] what really came to Africa… is around 0.1%. What is making us not to attract this kind of funding?”
Investors need assurance that their money is secure under predictable regulation.
“Any investor putting in is guaranteed that… the regulatory environment is protectionist to the investor in the local [market]… So in terms of regulation, for any investor to come, there has to be clarity. And this [policy work] is what we are doing here.”
Financing AI: Beyond Policy to Resources
Policy alone is not enough. AI infrastructure and talent are capital‑intensive, requiring explicit financing models.
“The infrastructure is capital intensive, the skills upgrading is going to be rapid, the technology is overtaking us in many aspects… We don’t have a brilliant policy that does not have the resources.”
Government officials stressed that financing must be private‑sector led, with the state focused on creating an enabling environment. A dedicated private sector roundtable is planned to align on investment opportunities, risks, and guarantees.
Capacity and AI Literacy: Public Sector Must Lead
Speakers emphasized that AI literacy and capacity‑building must begin with the education system.
“Capacity starts with owning the education system. There’s no private sector that can drive digital literacy and education like the public sector, nowhere in this world.”
Recommendations included:
- Establishing AI‑focused faculties or schools within universities.
- Building international and industry partnerships to accelerate skills.
- Setting clear 4–10 year horizons for producing world‑class talent.
Capacity was framed not only as technical expertise but also as national AI literacy and public trust.
“It all starts with understanding what is AI, how is AI going to be used, how is it going to benefit us… When people are more literate about AI… it also helps them in being comfortable enough… to use [it].”
Adoption: The Demand‑Side Challenge
Kenya’s AI ecosystem must focus not just on production but also on adoption.
“We are thinking about production, and sometimes we fail to recognize the other part that is essential for the use of AI within Kenya – consumption… Because once we develop these solutions, then who is supposed to use them?”
Speakers urged the policy team to address trust and bias concerns, encourage integration into existing workflows, and embed literacy and change management into the framework.
Environmental and Security Risks
Large‑scale AI infrastructure brings environmental and security challenges. GPUs consume vast amounts of energy and water, while e‑waste recycling remains underdeveloped.
“We’re building the infrastructure, and we are using a lot of GPUs… they consume a lot of energy, a lot of water, and now the e‑waste and recycling… we need to think practically here.”
Security risks were also flagged, with recent breaches underscoring the need for safeguards in public data‑sharing initiatives.
Long‑Term Vision
Officials stressed that Kenya’s AI policy is designed as a foundational, long‑term framework, guiding the country’s digital trajectory for decades.
“We are here to plan for the future… and we want to do it right… We make sure that whatever we output is relevant to the investor, is relevant to the donor, is relevant to anybody, even… a startup who wants to venture into the AI sector.”
