By Roger B. Jantio*
As policymakers, development institutions, and investors gather for the Spring Meetings of the World Bank Group and the International Monetary Fund, one question is gaining urgency: how should Africa finance its artificial intelligence ambitions?
Recent proposals have emphasized borrowing as a central tool. That may be part of the answer. But it is not where successful AI ecosystems begin.
Start with Value, Not Capital
The countries making real progress in AI did not start with large-scale borrowing or infrastructure build-outs. They started by creating systems that generate value—then allowed capital to follow.
That distinction matters.
India: Build the Rails First
India offers one of the clearest examples. Rather than investing heavily upfront in AI infrastructure, it built digital public infrastructure—identity, payments, and data-sharing systems.
These platforms enabled millions of daily transactions and created the foundation for a thriving ecosystem of applications. AI innovation emerged on top of that usage. Capital followed scale, not the other way around.
Estonia: Structure Before Scale
Estonia took a different path but reached a similar outcome. With limited resources and a small population, it focused on structuring how data and services interact across government and society.
Its digital backbone was designed for interoperability, not size. The result was an efficient, high-trust system where advanced applications, including AI, could develop organically.
Structure came before scale.
UAE: Capital with Direction
The United Arab Emirates provides a third perspective. Capital was available from the outset, but it was deployed with discipline.
Investments were tied to specific sectors, use cases, and partnerships. Infrastructure followed strategy, not ambition alone. This alignment reduced inefficiencies and accelerated execution.
Brazil and Indonesia: Applications Create Demand
In larger emerging markets such as Brazil and Indonesia, the path has been different again.
These economies did not lead in AI infrastructure. Instead, they built large-scale consumer platforms in areas such as fintech, e-commerce, and logistics. These platforms generated massive user bases and real transaction data.
AI is now being layered onto these ecosystems—enhancing services, improving efficiency, and unlocking new value.
Demand came first. Infrastructure followed.
What These Paths Have in Common
Across these examples, a pattern emerges.
None began by asking how to finance infrastructure. They began by building systems that create value, attract users, and generate data. Capital became effective because it was anchored in those systems.
What This Means for Africa
This has direct implications for Africa.
Borrowing, in itself, is not the issue. In classical economic terms, debt is justified when it finances assets capable of generating returns that exceed its cost.
The question, therefore, is not whether Africa should borrow to support its AI ambitions, but whether the systems being financed are designed to produce scalable and durable value.
If they are not, borrowing risks financing capacity without utilization.
If they are, capital—whether public or private—can be deployed more effectively and recycled over time.
From Infrastructure to Ecosystems
Africa’s opportunity in AI is unlikely to come from competing at scale in infrastructure. It lies in building applications, services, and platforms that respond to real demand—locally and globally.
That is where value is created. That is where ecosystems take shape.
From there, infrastructure becomes an enabler, not a starting point.
Getting the Capital Right
This also requires a broader evolution in how capital is mobilized and deployed.
Long-term equity capital, public-private collaboration, and disciplined structuring all have a role to play. But their effectiveness depends on the existence of systems that can absorb and scale that capital.
The Real Starting Point
Africa does not lack ambition. It does not lack opportunity.
What it must ensure is that the foundation of its AI strategy is built on value creation—so that when capital is deployed, it accelerates growth rather than chases it.
The countries that are succeeding in AI did not wait for capital to lead. They built systems that made capital useful.
Africa can do the same.
*Sir Roger Jantio is the Senior Managing Director and CEO of Sterling Merchant Finance Ltd and affiliated investment funds, and an early investor in AI and frontier-tech ventures in the United States and beyond. He is also strategic advisor with over 36 years of experience in capital allocation and cross-border deal structuring across African markets. Roger is a graduate of Harvard Business School.
