Across Africa’s innovation landscape, Artificial Intelligence (AI) has emerged as a defining narrative. From Nairobi to Lagos and Kigali to Cairo, governments and innovators are uniting around a shared vision: that AI will drive the continent’s next wave of economic transformation.
This optimism has become institutionalised. The African Union recently introduced its Continental AI strategy, and at least a dozen African countries have developed national strategies and policies related to AI, with the overall aim of leveraging AI to catalyse economic prosperity. Indeed, Africa’s digital future is being reshaped in real time, with AI as one of the centrepieces.
However, beneath this enthusiasm lies a significant disconnect. The institutional discourse around AI in Africa largely mirrors global frames, underlined by an assumption that technological advancements made elsewhere should automatically benefit the continent. This assumption, that innovation is a rising tide that lifts all boats, has previously failed Africa, and it is at risk of failing again.
The imitation trap
Africa’s institutional approach to AI is fundamentally misaligned with the continent’s material and institutional realities. These policies and strategies, which should define the continent’s collective institutional posture on AI development, deployment, and use, generally invoke the priorities of Western countries and dwell on abstract normative principles like trustworthiness, ethics, and human-centricity, concepts that, while important, often float above the more urgent constraints facing the maximisation of the potentials of AI by African countries.
Where these regional and national strategies engage with critical pillars, such as skills development, data governance, responsible innovation, or regulatory harmonisation, they do so sparsely or ceremonially. Many of these policies set ambitious targets for various countries, such as becoming global AI hubs, accelerating development goals, and positioning as competitive players in the Fourth Industrial Revolution. However, they do little to outline clear and practical roadmaps for achieving these objectives.
Ultimately, instead of grounding policy in mechanisms of strategic leverage, many of these institutional documents remain focused on normative alignment and symbolic positioning. In doing so, they risk deferring the substantive arc of Africa’s AI growth to external actors, and whatever independent local private actors can somehow take up the gauntlet. For a technology claimed to be key to leapfrogging some of the continent’s biggest challenges, this is far from ideal.
The key gaps
There are three ways African countries can optimise for AI-enabled growth: AI development, AI deployment, and AI adoption. These are not policy narratives; they are strategic priorities with concrete implications. AI development means the continent must be positioned to create AI technology so it can shape solutions that reflect its own realities. AI deployment involves a concerted institutional effort towards applying AI to real-world problems in key sectors like agriculture, health, and education, using clear public procurement and regulatory tools. AI adoption involves driving access to and use of AI by people in ways that enable co-creation, drive real-world problem-solving, and generate economic value.
For each of these, Africa operates at a deficit. In terms of development, limited computing infrastructure, persistent energy instability, a shortage of research ecosystems, and limited financing constrain the ability to build locally. AI deployment requires institutional capacity, coherent procurement systems, and integrated digital infrastructure that allow institutionally driven large-scale solutions, and these are lacking in many national contexts within Africa. AI adoption, which on its face appears to be the simplest lever, faces real constraints—limited connectivity, low mobile penetration, gaps in skills and knowledge, and affordability barriers—all of which mean those who need these technologies most are often least able to access them.
Policies of aspiration
Not minding these practical gaps, AI policies across the continent are filled with lofty promises, yet few offer any sense of how those promises will be achieved. Most lack credible costs or plans for addressing infrastructural constraints or developing the technical capacity required for AI development. When engaging with AI deployment, they do so from a 10,000-foot perspective, with vague, detached, and theoretical statements. Adoption is addressed through generic policy language borrowed from digital inclusion literature.
Where they do engage, many of these policies—or the discourse around them—fixate on developing large language models (LLMs) for African languages, as if that alone will solve the problem. But localisation is not the same as design, and mere access does not translate to autonomy.
Rethinking strategy: From aspiration to leverage
A credible “African” AI strategy does not become so because it contains the word “Ubuntu” or by listing a series of local, regional, or continental ambitions, unbothered by context. Instead, it must be honest about material constraints and transparent on how to surmount them towards an integrated collection of incisive results.
That means it must address, in itself or through accompanying documentation, the plans for building development capacity through investment in the infrastructure, talent, and data needed to create or adapt AI systems on African terms truly. It means providing clear roadmaps and clear costing plans for deploying AI in sectors like agriculture, healthcare, and education, where the impact can be immediate and locally meaningful. And it means taking adoption seriously, not as passive uptake, but as a strategic challenge tied to access, affordability, and usability, which can only be addressed through concrete concerted work.
The decade that decides
The global rules for AI are currently being written. Infrastructure is consolidating, standards are hardening, and value chains are crystallising. If Africa continues to skim over its material realities in favour of aspirational language, it will lock itself out of the foundational gains of another industrial revolution.
But the window remains open. Africa can still take the more challenging but necessary path by building infrastructure to position it for agency, investing in local use cases that actually position countries to leapfrog, and using policy as an organising principle, not for symbolism.
AI is not destiny; it is contested ground. And in every contest of power, those without leverage are not participants; they are subjects of others’ ambition. Africa must decide now which side of that equation it intends to occupy.
About the author:
Vincent Okonkwo is a lawyer and researcher whose work spans corporate governance, technology regulation, and digital/AI policy. He is a graduate of Harvard Law School and a former fellow of the Internet Society’s IGF Youth programme.
