Unleashing the AI jobs revolution in Africa

The conversation about artificial intelligence in Africa is currently dominated by a single, terrifying narrative: The U.S. and China control over 90% of the world’s AI computing power, leaving Africa at risk of becoming a “digital colony.” That would make the continent dependent on AI infrastructure and models built elsewhere.

The problem is real, and the conventional solution calls for a supply-side road map: building more data centers, training more data scientists, and creating more AI research hubs to build the engine of a new economy. But my biggest concern is that Africa is focusing almost exclusively on building the supply of AI talent without also unlocking the demand for it. It feels like we are training an army of world-class chefs for a city with no restaurants. Without a robust local market that can absorb this new talent, we are simply training our best minds for export.

I’ve argued before that generative AI unbundles old professions by isolating and automating the tasks in them. For the West, this unbundling is an existential threat. It means the painful dismantling of legacy institutions, the devaluation of expensive credentials, and a chaotic transition for a workforce trained for a world that is rapidly disappearing.

But for countries that were largely excluded from that old model, the dynamic is entirely different. They are not burdened by the same institutional inertia, nor are they emotionally wedded to the old definitions of prestige. They don’t have to endure the crisis of the old system collapsing because they were never fully integrated into it in the first place.

What looks like a painful deconstruction in the West could simply be the arrival of a better, cheaper, and more scalable system for everyone else. It is not a collapse, but a new foundation on which they can immediately start to build.

As an American born in Ethiopia, I’ve spent my life straddling two different systems. I climbed the ladder of Western meritocracy while witnessing my country of birth — and the African continent — grapple with a professional scarcity so deep, it renders opportunity invisible.

For a farmer in rural Ethiopia, the scarcity tax isn’t a line on a spreadsheet —  it’s a field lost to a preventable crop disease for lack of an agronomist. For an entrepreneur in Lagos, it’s a business ruined by a bad contract and no access to legal help. For a mother in Kampala, it’s a child’s treatable illness that turns fatal without a doctor nearby.

For decades, the Global South has paid this uncounted tax in lost potential, lost livelihoods, and lost lives.

Ethiopia , home to over 120 million people,  has fewer than 10,000 physicians. There are more Ethiopian-trained doctors in cities like Washington, D.C., and Chicago than all of Ethiopia. The country trains medical professionals, but loses them to global demand — a stark example of brain drain. It is not a failure of talent; it’s a failure of systems.

We don’t just lack professionals, we lack the jobs for them — essential roles that never emerged because the cost of creating them, and retaining them, is prohibitively high.

Here’s where AI can make a difference. A common criticism is that powerful AI is expensive to build and deploy. This is true, but it misses the point of scale. The cost of an AI-driven diagnostic analysis is a tiny fraction of what’s required to train, pay, and retain a traditional radiologist. This massive cost reduction is what makes it economically viable, and helps deliver a jobs dividend.

It doesn’t eliminate the need for experts; it creates a new, multilevel professional ecosystem. 

Here’s how it would look: At the first level, we may have a micro professional. This is where the Global South’s greatest asset —  its abundant and youthful labor force — can be trained quickly to deliver high-volume services at the community level, augmented by AI.

Imagine a health worker in rural Uganda using an AI diagnostic app to monitor chronic conditions across an entire district. Or an agronomist in Ethiopia leveraging drones and AI to advise hundreds of farmers each week on crop disease. Or a paralegal in Lagos offering affordable contract reviews to small businesses via WhatsApp, backed by localized legal models.

At the second level, traditionally trained experts can be freed from mundane tasks so they can operate at the top of their ability. Their roles become even more critical. We will need more of them to manage the most complex cases, to train and supervise this new AI-assisted workforce, and to provide essential human oversight and ethical governance for the systems. Their expertise is thus not replaced, but elevated and scaled.

This isn’t a zero-sum game of replacement. It’s the creation of an entirely new, more inclusive, and more efficient system for developing and deploying human expertise.

This future is not inevitable; it has to be deliberately built. The capital we need will not be granted by mandate; it will be earned by results. Capital goes where there are returns to be had. Our job is to create those returns. If we can successfully unlock the local demand for these new AI-driven services, creating a vibrant market, the investment will follow.

The good news is, this is already starting to happen. We have a new generation of nimble, AI-focused funds like Lava VC and new local powerhouses like Future Africa. They are part of the very ecosystem that leaders like Vukosi Marivate are building with AI companies like Lelapa AI. Tools such as Ubenwa — which uses AI to analyze a newborn’s cry for signs of birth asphyxia — are already showing how innovation can fill critical care gaps.

But to truly unleash a jobs revolution, a second catalyst is required. Our largest corporate champions — companies like MTN, Safaricom, Ecobank, and Access Bank — must step up to become the first investors and customers for this new wave of innovation. With their vast distribution networks and deep market understanding, they have a rare opportunity not just to participate in this new ecosystem but to help build it — and benefit immensely in the process.

This requires a new regulatory system. We must build frameworks that judge innovators on their effectiveness, not just their credentials. And we must build our own models, fine-tuned for local languages, cultures, and realities. This is how the Global South shifts from being merely data suppliers to being innovators.

Leaders in the Global South face a generational choice: cling to outdated rules that protect the few who escaped the scarcity trap, or design new systems that will unlock the potential of the many. This opportunity is fleeting. The foundations of the next global economy are being built right now, and we must decide if we want to design our own future, or if we simply remain a tenant in a house that we did not build.

These are not speculative ideas for future employment; they already exist, latent and anchored in unmet demand. The current economics have simply forced them to remain invisible. Remove the bottlenecks and they will appear, with the market quickly funneling capital, talent, and other resources to unleash them.

Engaging now  requires a new regulatory imagination. It means creating faster pathways to professional legitimacy, and building the digital public infrastructure to support AI-augmented services at scale. The greatest opportunity of the 21st century is not to disrupt the old jobs of the West. It is to finally create the millions of jobs the rest of the world needs.