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\nBy Sir Roger Jantio, Senior Managing Director & CEO, Sterling Merchant Finance Ltd, Washington, DC<\/em><\/p>\n<\/blockquote>\n
As African finance ministers gather for the Spring Meetings of the International Monetary Fund and the World Bank next week in Washington, DC, the question of how to finance the continent\u2019s artificial intelligence ambitions has moved from aspiration to urgency. In that context, the recent call by the United Nations Economic Commission for Africa for African countries to expand borrowing, strengthen domestic resource mobilization, and leverage institutional capital to fund AI-related infrastructure is both timely and important.<\/p>\n
The report the Commission released on April 2 highlights a real and pressing gap. It calls on African governments to expand borrowing, strengthen domestic revenue mobilization, and leverage institutional capital to finance investments in data centers, energy systems, and digital infrastructure. Africa accounts for a negligible share of global data center capacity, faces structural energy constraints, and lacks the digital infrastructure required to fully participate in the emerging AI economy. Public budgets alone are insufficient to meet these needs, and new sources of financing must be mobilized.<\/p>\n
This diagnosis is correct. The urgency is real. And the ambition\u2014to ensure that Africa captures value from AI rather than remaining a passive participant\u2014is both necessary and commendable.<\/p>\n
Yet the conversation must now move one step further.<\/p>\n
From Financing Needs to Financing Strategy<\/strong><\/p>\n
Africa needs capital. It needs significant capital to build infrastructure, support innovation, and enable scale. But capital alone, particularly when deployed without a clear framework for value creation and capture, does not constitute a strategy.<\/p>\n
The current approach to finance AI in Africa\u2014centered on borrowing, revenue mobilization, and blended finance\u2014addresses the source of funds<\/strong>. It does not yet fully address the structure of value creation<\/strong>.<\/p>\n
This distinction is critical.<\/p>\n
Across multiple sectors, Africa\u2019s development experience has shown that financing inputs without clearly defined monetization pathways often leads to constrained returns, fiscal pressure, and underperforming assets. The risk is not borrowing per se. The risk is borrowing into systems that are not yet structured to generate scalable and replicable value.<\/p>\n
The Limits of an Infrastructure-First Model<\/strong><\/p>\n
The emphasis on data centers, energy systems, and digital infrastructure reflects a widely held view: that participation in the AI economy requires building the same foundational assets that underpin AI ecosystems in the United States or China.<\/p>\n
There is truth in this. Infrastructure matters.<\/p>\n
But an infrastructure-first model, when not paired with a clear strategy for value capture, risks placing Africa in a capital-intensive race where others retain structural advantages in scale, technology, and financing capacity.<\/p>\n
Africa\u2019s opportunity may lie less in replicating these systems at scale, and more in identifying where it can generate high-value applications, services, and outputs<\/strong> that are competitive globally.<\/p>\n
In that context, infrastructure becomes an enabler\u2014not the strategy itself.<\/p>\n
From Inputs to Systems: A Strategic Reframe<\/strong><\/p>\n
What is required is a shift from a financing conversation centered on inputs to one centered on systems.<\/p>\n
Rather than thinking in linear terms\u2014mobilize capital, build infrastructure, and expect growth\u2014Africa\u2019s AI strategy must be organized around how value is created, captured, and scaled.<\/p>\n
This implies a different sequencing:<\/p>\n
structure \u2192 monetize \u2192 scale \u2192 finance<\/strong><\/p>\n
In this model, financing follows from clearly defined pathways to revenue generation and value capture. It is anchored in systems that are designed from the outset to produce economic returns, rather than relying on those returns to emerge over time. In practice, this means shifting from financing assets in isolation to structuring ecosystems in which revenue generation, scale, and capital recycling are embedded from the outset.<\/p>\n
The Role of Structure in Capital Deployment<\/strong><\/p>\n
This is where the next phase of the conversation must evolve.<\/p>\n
Africa does not face a binary choice between public financing and private capital. Nor is the solution simply to increase the volume of funding available. The more fundamental challenge lies in how capital is organized, deployed, and linked to value creation.<\/p>\n
Public-private partnerships, when properly structured, can play a central role\u2014not merely as financing mechanisms, but as platforms for aligning incentives, distributing risk, and enabling scale. Similarly, institutional investors\u2014pension funds, sovereign funds, and others\u2014can contribute meaningfully when opportunities are framed in ways that reflect predictable revenue streams and disciplined structures.<\/p>\n
The private sector, and in particular experienced capital allocators, must therefore be part of the design process from the outset. Their role is not only to provide capital, but to help shape the mechanisms through which that capital is translated into sustainable economic value.<\/p>\n
Financing What Scales<\/strong><\/p>\n
A key implication follows: not all AI investments are equal.<\/p>\n
Investments that remain localized, fragmented, or dependent on continuous public support will struggle to generate the scale required to justify large capital outlays. By contrast, investments that are designed to scale\u2014across markets, across use cases, and across time\u2014create the conditions under which capital can be deployed more efficiently and recycled.<\/p>\n
In that sense, the objective is not only to finance projects, but to finance systems that can expand and replicate<\/strong>.<\/p>\n
Africa needs capital\u2014and it needs capital that is structured to scale.<\/p>\n
Toward a More Complete Framework<\/strong><\/p>\n
The UNECA report has performed an important service by elevating the urgency of financing Africa\u2019s AI future. It has placed the issue squarely on the agenda of policymakers at a critical moment.<\/p>\n
The next step is to build on that foundation by integrating a more explicit focus on value creation, monetization pathways, and capital structuring.<\/p>\n
This does not replace the need for borrowing, domestic resource mobilization, or blended finance. It complements them\u2014by ensuring that the capital mobilized is deployed within systems designed to generate returns, reduce risk, and sustain growth.<\/p>\n
Conclusion<\/strong><\/p>\n
Africa stands at an inflection point in its engagement with artificial intelligence. The choices made now\u2014about how to finance, structure, and scale its participation\u2014will shape outcomes for years to come.<\/p>\n
The question is no longer whether capital can be mobilized. It is whether that capital can be organized in ways that translate ambition into durable economic value.<\/p>\n
If that alignment is achieved, financing will follow\u2014and scale will become not an aspiration, but a repeatable outcome.<\/p>\n
Roger B. Jantio<\/strong>\u00a0is an AI investor and strategic advisor. He is the founder and CEO of Sterling Merchant Finance Ltd and affiliated investment funds and a graduate of Harvard Business School.<\/p>\n<\/div>\n
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