As artificial intelligence reshapes industries globally, questions continue to emerge about Africa’s place in the AI economy—not merely as a consumer market, but as a creator of competitive AI companies.
For Jephte Ioudom Foubi, this question is not theoretical.
The Cameroonian-born data engineering consultant and founder has worked on enterprise digital transformation, building AI and data infrastructure solutions for organisations including BASF, Euroclear, GSK, and Unilever. From deploying AI systems across 80+ countries to leading transformation projects in Europe, Foubi brings technical depth and an African perspective to the conversation.
In this interview, he shares what Africa must get right to compete in the global AI race. Excerpts.
There is growing excitement around AI globally. Do you believe Africa can genuinely build globally competitive AI companies?
I absolutely believe so. Africa has the core ingredients such as intelligent talent, entrepreneurial resilience, complex local problems that demand innovation, and increasingly connected digital populations.
What is often missing is not capability, but structure.
Globally competitive AI companies are not built on talent alone. They require infrastructure, access to capital, world-class engineering discipline, distribution channels, and ecosystems that support long-term execution.
Africa can absolutely build such companies, but the conversation must shift from optimism to institution-building.
What gives you confidence in Africa’s AI potential?
I have worked with some of the world’s most sophisticated enterprises, and one thing that becomes very clear from those experiences is that talent is globally distributed.
African engineers can absolutely compete at any level. In fact, many already do, but often remotely, and invisibly.
However, what gives me confidence is that Africa’s technical talent is stronger than global perceptions suggest.
What we need is an environment where that talent builds category-defining companies locally rather than exporting its best capabilities abroad.
What are the biggest barriers preventing Africa from producing globally competitive AI companies?
In my opinion, there are at least three things. The first is infrastructure. AI requires robust compute access, cloud maturity, data systems, and reliable digital environments.
The second is patient capital, which is not quite lacking in Africa, but not sufficiently abundant yet. AI companies are not quick-flip startups. They are deep technology that requires time and long-term investment.
And the third barrier, I would say is execution culture. Building global AI businesses requires engineering rigour, product discipline, governance, and operational excellence, and not just ambition.
Talent without systems rarely scales.
Some argue Africa should focus on AI applications rather than foundational AI. Do you agree?
I’d say yes to an extent, but with nuance. Africa does not need to compete immediately in training trillion-parameter foundational models. That is capital intensive and strategically difficult.
But AI applications? Absolutely. Enterprise automation, healthcare intelligence, logistics optimisation, agricultural intelligence, financial infrastructure, multilingual AI, present huge opportunities.
Global competitiveness does not always have to mean building the base model. It could mean owning valuable application layers.
Based on your enterprise experience, what separates serious AI companies from hype-driven ones?
Execution. Execution. Execution. Currently, everyone talks about AI, but very few are executing with the seriousness and discipline required.
Serious companies solve measurable business problems. They think in terms of reliability, scalability, governance, integration, and ROI.
In enterprise environments, AI hype dies quickly if systems fail, hallucinate, or create operational risk. The winners are not the loudest, but they are the most disciplined.
What role should governments and policymakers play?
I believe that policymakers and African governments have critical roles to play beyond flamboyant and fancy speeches about the potential impact of AI on the continent.
They should think beyond that.
Some of those practical priorities should include investing in critical digital infrastructure, cloud and data ecosystem support, AI education, startup-friendly regulation, research partnerships, procurement pathways for local innovation, etc.
They earlier that policymakers understand that strong ecosystems do not emerge by accident, but are engineered, the faster Africa can move towards attaining the goal of creating globally competitive AI companies.
Can Africa compete globally while solving local problems?
That is exactly how it should compete. Some of the strongest global companies emerged by solving highly specific problems well.
I would argue that has a plethora of unique challenges, such as fragmented logistics, informal economies accounting for up to 83% of employment. Then we have the unique challenge of multiplicity of language, financial inclusion gaps, and a dearth of infrastructure financing estimated at over $170 billion. All these has led to massive inefficiencies that significantly reduced economic growth on the continent, and I do believe these challenges to be innovation opportunities.
Solve some of these hard, local problems elegantly, and many of the solutions become globally relevant.
What advice would you give African AI founders?
My only advice at the moment to founders is to build substance before storytelling. Too many founders focus on hype, funding narratives, and visibility.
It is not that those are not important, but AI is unforgiving. You need strong technical foundations, deep customer understanding, execution discipline, and clear monetisation pathways to stand a chance. The hype could come after you figure out some of these factors.
And importantly, build globally from day one in terms of standards, product thinking, and engineering quality.
Is Africa at risk of becoming merely a consumer of foreign AI products?
Yes, very much so. If we do not intentionally build our own capabilities, that becomes the default outcome.
AI will shape productivity, commerce, communication, and governance. There is no doubt about that. It’s a only a matter of time.
The regions that only consume imported intelligence systems will have limited strategic influence over how those systems evolve.
This is not just a commercial issue. It is a competitiveness issue.
What would success look like over the next decade?
Success would mean seeing African AI companies serving global customers at scale.
It would mean enterprise software companies emerging from Africa, not just service providers.
It would mean technical founders building enduring institutions.
And it would mean the global technology conversation no longer treating African innovation as surprising.
The goal is not, and should not be participation. The goal is leadership.
