–By Sola Adebawo
For decades, Africa’s place in the global economy has largely followed a familiar pattern.
The continent supplied raw materials. Others controlled processing, financing, technology, branding, and the highest layers of value creation. Minerals left Africa as ore and returned as expensive finished products. Oil left as crude and returned as refined fuel. Agricultural commodities departed cheaply and reappeared within global consumer brands.
Now, a new extraction economy is emerging. But this time, the resource may not lie beneath African soil. It may lie within African intelligence itself.
Artificial intelligence is rapidly becoming the infrastructure of modern economic power. Yet beneath the excitement surrounding AI tools and digital transformation sits a deeper geopolitical question Africa must confront early:
Will Africa become a creator within the AI economy, or merely a source of raw digital value for systems owned elsewhere?
This question is no longer theoretical.
Every day, millions of Africans generate enormous amounts of digital data through mobile banking, social media activity, e-commerce, location services, voice recordings, biometric systems, and online behaviour. That data increasingly powers global AI systems, trains algorithms, strengthens foreign platforms, and expands the dominance of technology ecosystems largely headquartered outside the continent.
In effect, Africa risks becoming a supplier of raw cognitive resources within the digital economy.
The mineral age extracted physical resources. The AI age may extract behavioural and intellectual value.
The scale of the issue is significant because Africa’s demographic trajectory gives it enormous long-term strategic relevance. The continent is projected to account for nearly one-quarter of the world’s population by 2050, with the world’s youngest population and one of the fastest-growing digital user bases. At the same time, mobile connectivity continues to expand rapidly across African markets.
Yet participation alone does not guarantee value capture.
This is where Africa faces a critical strategic challenge.
Despite its demographic advantages, Africa currently accounts for less than 1% of global data centre capacity, according to industry estimates. Much of Africa’s digital activity still depends heavily on foreign-owned cloud infrastructure, offshore data hosting, and externally controlled computing systems.
That dependency matters more in the AI era because AI is fundamentally an infrastructure game.
Power no longer rests only in software applications. Increasingly, it rests in:
- cloud infrastructure
- compute capacity
- semiconductor access
- data centres
- fibre networks
- electricity reliability
- large language models
- advanced research ecosystems
Countries and regions that control these layers will shape future economic hierarchies.
Those that do not may find themselves permanently positioned at the lower end of digital value chains.
The global race for AI dominance has already triggered massive infrastructure competition among major powers. The United States, China, Europe, and Gulf economies are investing aggressively in compute infrastructure, semiconductor capability, sovereign AI systems, and domestic cloud ecosystems.
Africa, meanwhile, still faces significant infrastructure gaps.
According to the Africa Data Centres Association, the continent requires at least 1,000 megawatts of new data centre capacity across hundreds of facilities to meet growing demand. McKinsey estimates that Africa’s data centre demand could rise between 3.5 and 5.5 times current levels by 2030, requiring between $10 billion and $20 billion in investment.
This is not simply a technology story. It is a sovereignty story.
Data increasingly shapes finance, security, education, healthcare, commerce, media visibility, and political communication. Countries that do not shape digital systems risk eventually being shaped by them.
One important dimension of this conversation involves language and cultural representation.
Most large language models are trained predominantly on Western and globally dominant datasets. African languages, local governance realities, historical contexts, and cultural frameworks remain significantly underrepresented in many foundational AI systems.
That creates the risk of algorithmic invisibility.
If African realities are weakly represented in global AI systems, then future digital tools may increasingly interpret African societies through external assumptions and incomplete datasets. Over time, this affects everything from educational content to automated decision-making systems and knowledge production.
Civilisations absent from technological architecture eventually become dependent on architectures designed by others.
This is why Africa’s AI conversation cannot remain limited to digital adoption alone.
The continent must also think seriously about digital sovereignty.
This does not mean technological isolationism or hostility to foreign investment. Africa needs global partnerships, capital, innovation networks, and technology transfer. Indeed, some positive momentum already exists. Microsoft recently announced plans to train one million South Africans in AI and cybersecurity skills by 2026, while major cloud providers continue expanding African infrastructure footprints.
But there is an important difference between integration and dependency.
Africa has experienced this distinction before in earlier economic eras.
The challenge now is whether the continent can position itself differently before digital hierarchies become entrenched.
Some countries are beginning to recognise the stakes. South Africa, Kenya, Nigeria, Rwanda, and Egypt are increasingly emerging as regional digital infrastructure hubs. South Africa, in particular, is attracting growing AI-related data centre investment linked to cloud expansion, renewable energy integration, and national AI strategy discussions.
Still, the broader continental response remains fragmented.
Many African governments have not yet fully integrated AI into long-term industrial policy, labour strategy, national competitiveness planning, or economic sovereignty frameworks. Universities remain underfunded relative to the scale of global AI competition. Local AI research ecosystems are still developing. Electricity instability continues to constrain large-scale compute infrastructure in many markets.
Meanwhile, global technology consolidation is accelerating.
The risk is not necessarily exclusion from the AI economy. Africa will almost certainly participate. The deeper risk is participating primarily as a low-value data supplier and digital consumer while ownership, compute power, advanced modelling, and economic capture remain concentrated elsewhere.
This is precisely how extraction economies reproduce themselves.
History rarely repeats itself in identical forms. But it often reproduces familiar structural relationships beneath new technologies.
The AI era therefore presents Africa with a narrow but important strategic window.
The continent can still shape parts of its digital future because the architecture of global AI governance remains unfinished. Regulatory frameworks are evolving. Infrastructure competition is still expanding. Indigenous language modelling remains underdeveloped globally. Digital public infrastructure conversations are still open.
But this window will not remain open indefinitely.
Africa must therefore approach AI not merely as a technology trend, but as a long-term political economy issue involving sovereignty, capability, infrastructure, and ownership.
The continent’s greatest long-term advantage may ultimately be its people. Africa’s youthful population, entrepreneurial adaptability, linguistic diversity, and rapidly expanding digital ecosystem are extraordinary strategic assets in the knowledge economy.
But demographics alone do not create power.
Institutions do. Infrastructure does. Strategy does. Ownership does.
And the central question confronting Africa may ultimately be this:
Will the continent help build the systems of the future, or merely supply the raw human intelligence that powers them elsewhere?
Because the next scramble for Africa may not begin with territory.
It may begin with data, computation, and digital dependency.
Sola Adebawo is an energy executive, institutional strategy, and public affairs leader with deep experience at the intersection of energy, governance, policy, and strategic communication. He currently leads Hyphen Partners Limited, a specialist advisory firm supporting organisations navigating complex, policy-sensitive environments. His writing explores reform, political economy, leadership, culture, and the relationship between institutions and public life. He is an author, scholar, and ordained minister.
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