The ATU Ministerial Forum at AfricaTech 2025 in Cape Town wasn’t really about artificial intelligence. It was about legitimacy — about who gets to narrate Africa’s digital destiny, and who gets written out of it.
The keynote unfolded with the expected precision: a continent standing at the edge of an “intelligent era,” governments pledging to build systems that “work for Africa.” But beneath the calm technocratic tone was something more interesting — a quiet assertion of power. This wasn’t a tech briefing; it was a declaration of intent.
The Minister’s framework — values, capabilities, cooperation — reads like a diplomatic algorithm: tidy enough to agree on, vague enough to interpret however you like. Each term carried weight, but none landed with specifics. That’s the genius and the flaw of continental policy language. It sounds like consensus, even when there isn’t any.
Local intelligence, global dependencies
The phrase “African AI” is already loaded. It implies not just local data or indigenous design, but a break from dependency — a continent building its own systems, in its own languages, for its own needs. The keynote hit that note repeatedly: AI must work for Africa, in Africa’s languages, for African use cases.
It’s an appealing idea, but it collapses under inspection. There’s no sovereign cloud, no open-access compute, no hardware independence. Most African countries still lease the digital foundations of their economies from foreign providers — the same few American and Chinese firms that define AI elsewhere.
So when ministers call for “models trained on African data,” they’re really describing a kind of digital nationalism without the machinery to support it. The infrastructure to train those models — from GPUs to stable power — is still imported, rented, or conditional. The result is that African AI can be African in spirit, but rarely in substance.
The risk isn’t that the vision is too ambitious; it’s that it mistakes localisation for autonomy. You can build an isiZulu chatbot on Amazon’s servers, but it still belongs to Amazon’s logic.
Data, dignity, and selective morality
To their credit, the Minister named the dangers — surveillance, manipulation, discrimination — and grounded AI ethics in human rights, not just innovation. But ethics at the policy level often becomes performance: a checklist for legitimacy.
The forum’s moral register was clear enough: Africa’s AI must expand freedom, not restrict it. But the question never quite landed — freedom for whom, from whom? When governments promise AI that strengthens democracy, it’s worth asking how many of them are building the digital tools that monitor dissent.
This gap between the ethical posture and political practice isn’t unique to Africa; it’s global. But in a region where digital policy is often written faster than it’s implemented, it’s particularly stark.
The continent’s rhetoric of protection — of “fair compensation,” of “lawful use of cultural knowledge” — gestures at dignity, but rarely addresses enforcement. Once your language, folklore, or community data enters the training pipeline, good luck tracing where it went. “The depth of our heritage is not a free input,” said the Minister. It’s a good line. But as with most good lines, it risks being more symbolic than operational.
The slow politics of infrastructure
The forum kept circling back to infrastructure — fibre routes, data centres, regional energy grids — as if the right configuration of cables could produce equality. Infrastructure, here, was both metaphor and mirage.
It’s not wrong to want local compute or interoperable standards. But the idea that Africa’s AI future hinges on data centres misses a deeper truth: infrastructure is not neutral. Whoever owns it sets the conditions of participation.
In that sense, “cooperation” — the keynote’s third pillar — is less a virtue than a vulnerability. Every cross-border data route invites the question of trust; every shared cloud becomes a geopolitical wager.
The African Continental Free Trade Area was cited as the vehicle for this coordination. Maybe it will be. Or maybe, like many such frameworks, it will remain aspirational until someone decides it’s profitable.
As I noted in my piece on Google’s AI in Action 2025, the politics of localisation aren’t just linguistic — they’re existential. “This isn’t localisation for press shots,” that piece observed, “it’s a nod to the reality that most global tech overlooks.” What we build physically — cables, servers, data routes — ends up shaping what we can imagine politically. The forum’s insistence on connectivity sounded practical, but it was also a way to avoid the harder question of ownership.
Contribution versus consumption
There was a refrain that echoed through the room: Africa must not just consume technology; it must contribute to it. The line drew nods because it flatters both policymakers and investors. It sounds assertive, but it’s vague enough not to threaten anyone.
In practice, “contribution” means participating in global research pipelines dominated by others. It means entering supply chains that extract value from African inputs — data, culture, labour — while offering “collaboration” in return. The Minister’s call for joint intellectual property and reciprocal access is exactly right; it’s also exactly what global partners are least willing to offer.
This is the paradox of the African AI future. To be included, the continent must first agree to the conditions of inclusion. And those conditions are rarely written in its own favour.
The wisdom trap
The keynote closed with a neat aphorism: “The intelligent era should not be defined by how intelligent our machines become, but by how wise our choices are.” It landed well — too well. Wisdom is a generous word, but a convenient one. It asks for reflection, not redistribution.
The danger in all this talk of “values” and “wisdom” is that it risks turning power into philosophy. The continent doesn’t need to be wiser; it needs to be less dependent.
If Africa’s AI future is to mean anything, it won’t come from summits or slogans. It will come from deciding whose servers we trust, whose data we protect, and whose definition of intelligence we’re willing to internalise.
Until then, “African AI” remains less a technological project than a political one — and politics, as everyone in that Cape Town hall knew, is the only system that never really learns.