By Harrison Muiru
Across Africa, the conversation on artificial intelligence has shifted from curiosity to urgency. Governments are developing national AI strategies, private sector players such as healthcare providers and insurance players are investing in innovation, and development partners are positioning AI as a driver of economic growth. Yet, despite this momentum, adoption across the continent remains uneven—fragmented in execution and, in many cases, confined to pilots rather than scaled systems.
The missing link is not ambition. It is policy.
Research by the World Bank and International Finance Corporation highlights that digital technologies, including artificial intelligence, achieve scale and impact only where enabling regulatory frameworks, institutional capacity, and investment environments are aligned. AI does not scale in isolation; it scales within the guardrails, incentives, and direction set by policy. In an Africa context where markets are diverse, regulatory environments are evolving, and infrastructure gaps persist – policy is not merely an enabler; it is the primary accelerator of adoption.
From Possibility to Practicality: Why Policy Matters
Artificial intelligence holds immense potential to transform key sectors across the continent; from healthcare and agriculture to financial services and public administration. However, without clear and coherent policy frameworks, this potential remains largely theoretical.
Policy performs three critical functions that determine whether AI moves from concept to impact. First, it creates certainty. Businesses invest where there is clarity. Well-defined regulatory frameworks around data governance, AI ethics, and digital infrastructure reduce ambiguity and unlock private sector confidence thus driving the adoption. Second, it aligns priorities. AI must be directed toward solving real, systemic challenges – improving healthcare access, strengthening financial inclusion, and enhancing public service delivery. Policy ensures that innovation is anchored to national and regional development goals rather than isolated experimentation.Third, it builds trust. AI systems rely on data that is often sensitive and high-stakes. Without robust frameworks for privacy, security, and accountability, adoption will inevitably be constrained by skepticism and resistance.
In essence, policy transforms AI from a technological capability into a scalable public good.
The Kenyan Context: Legislative Momentum and the AI Bill, 2026
To understand how policy accelerates adoption, let’s look at Kenya, often called the Silicon Savannah. We have moved beyond conversation into concrete legislative action. In March 2025, the Ministry of ICT published a National AI Strategy (2025–2030), requiring an investment of KSh 152 billion to position Kenya as a leading AI hub. The strategy explicitly recognizes “a need for comprehensive AI-specific regulations to address ethical implications and potential harms.” Building on this foundation, the Artificial Intelligence Bill, 2026, on the floor of senate, is currently undergoing public participation. The Bill proposes a risk-based framework similar to the EU AI Act, classifying AI systems from “unacceptable risk” to “minimal risk.”
However, the African context demands unique solutions. As the Bill undergoes debate, stakeholders have cautioned that rigid frameworks risk unintended consequences. One observer noted, “The developer in Nairobi is not asking for exemption from accountability. She is asking for a framework designed with her in mind. A framework that governs everyone except the most powerful is not governance.” This tension captures the essence of Africa’s AI policy challenge: how to regulate without stifling innovation.
The Role of Business Leaders: From Participants to Co-Creators
For too long, the private sector has been positioned as a recipient of policy rather than a co-creator of it. In the context of AI, that model is no longer viable. Business leaders operate at the frontlines of implementation. They understand where systems break, where inefficiencies persist, and where innovation can deliver measurable value. This insight is indispensable in shaping policies that are both practical and effective.
Technology adoption accelerates when policy and practice are aligned and achieving this alignment requires deliberate engagement. Business leaders must actively contribute to policy development by engaging regulators, providing evidence-based insights, advocating for balanced frameworks, and supporting capacity building within public institutions. In doing so, the private sector evolves from stakeholder to strategic partner in national development.
Bridging the Gap
Africa does not lack AI conversations. Conferences, summits, and policy frameworks are increasingly common. The challenge lies in translating dialogue into delivery.
To accelerate adoption, three critical shifts are required. First, from policy announcements to policy execution. Strategies must be accompanied by clear implementation frameworks, defined timelines, and accountability mechanisms. Kenya’s shift from a national strategy to the AI Bill, 2026, represents progress, though critics warn of potential regulatory overreach if not carefully calibrated to local realities. Second, a move from siloed efforts to ecosystem collaboration. The Bill’s proposal for an Advisory Committee on AI, comprising government, non-governmental, and private sector stakeholders, is a step toward coordinated governance. Third, a move from short-term pilots to scalable systems. AI solutions must move beyond proof-of-concept and integrate into core institutional processes, whether in insurance automation, clinical decision support, or claims management.
A Call to Action
The future of AI in Africa will not be determined solely by technological capability. It will be shaped by the quality, clarity, and adaptability of policy. If we get policy right, AI will drive efficiency across critical sectors, expand access to essential services, and unlock new economic opportunities. If we get it wrong, adoption will remain fragmented, trust will erode, and the full value of AI will remain unrealized.
The responsibility, therefore, is collective.
Governments must lead with clarity and intent. The private sector must engage with purpose and accountability. And together, stakeholders must build policy frameworks that are not only enabling but also transformative. Because ultimately, AI is not just about technology. It is about how we design and govern the systems that will define our future.
The author is the Group Managing Director, Smart Applications International – a leading health-tech ICT solutions provider.
