By Simon Poole, Non-Executive Director and AI Advisor to Boards across Africa. Former Operating Partner, Helios Investment Partners.

There’s a growing narrative that Africa is being “left behind” in the global AI race, particularly in the development of large language models (LLMs). I believe this concern is misplaced. Africa is uniquely positioned to accrue outsized benefits from AI and, in some areas, leapfrog ahead.

Why LLMs are not where the value lies

In my analysis of AI, particularly generative AI, the long-term value will not come from building LLMs, but from using them. Whether it’s operating companies, governments, or individuals, the greatest gains will accrue to users of AI, not model developers.

The models themselves have no unique, defensible technology apart from scale. And even that advantage is diminishing as training techniques become more efficient. Building an LLM will not, in itself, deliver sustained competitive advantage. Microsoft, Google, X, Meta, OpenAI, Anthropic, Mistral, and DeepSeek have already developed powerful models. Amazon, Baidu, Apple, and Alibaba are close behind. With so many players entering the field, the models will become commoditized.

While there are nuances among the models’ capabilities, these differences will diminish over time. Any model that attempts to charge a significant premium risks losing market share. This shift means that the real opportunity lies in applied AI.

There’s a growing narrative that Africa is being “left behind” in the global AI race, particularly in the development of large language models (LLMs). I believe this concern is misplaced.

Applied AI in Africa

The users of LLMs, governments, startups, and institutions, will apply them to improve education, healthcare, utilities, and more. In Africa, many of these challenges are more urgent than in other parts of the world. As a result, the impact of successful AI applications could be significantly greater.

Education

Africa faces a well-documented gap in educational access. Approximately 20% of African children have no access to primary school, double the global average. Many governments lack the resources to provide sufficient schools and qualified teachers. This issue is exacerbated by rapid population growth.

AI offers a compelling solution. It’s well established that the most effective way to learn is with a personal tutor. With access to a smartphone or connected device, a student can now benefit from an AI tutor. This isn’t just theory: in Benin City, Nigeria, the World Bank ran a trial in which children received supplemental tutoring through an AI-based system for six weeks. The results? Students made the equivalent of two years of academic progress in that short period.

Utilities

Power supply remains a persistent challenge across Africa. Among the key issues is that many electricity providers cannot collect revenue effectively, leaving them financially unstable and unable to invest in new generation capacity.

In Ghana, the Electricity Company of Ghana (ECG) has implemented AI and fintech solutions to address this problem. These tools have helped reduce fraud and improve collections. As a result, ECG’s revenue performance has significantly improved. This financial recovery creates the foundation for future investments in power generation, demonstrating how applied AI can unlock systemic progress.

Healthcare

Healthcare across many African countries suffers from inadequate infrastructure, a shortage of trained professionals, and a heavy burden of disease. Here, too, AI is making a difference.

Consider BabyChecker, an AI-powered, smartphone-connected ultrasound tool. Many pregnant women cannot access clinics for routine scans. With this tool, a community health worker can perform a scan, and the AI interprets it to assess gestational age, detect multiple pregnancies, and flag high-risk cases. In under-resourced settings, this technology can be lifesaving; in well-funded health systems, it might be merely convenient.

The leadership challenge

While many of these AI applications remain at pilot stage, the challenge now is to scale them. One of the biggest barriers is leadership. Many senior decision-makers have not grown up with AI and may be hesitant to embrace it. But the time for hesitation has passed.

Leaders must invest the time to understand AI’s potential, and then actively integrate it into their organisations. Those who can do this will be best positioned to shape the continent’s future. Those who can’t must empower a new generation of leaders to take up the challenge.

Simon can be reached at simonhpoole@hotmail.com or check out his LinkedIn profile at https://www.linkedin.com/in/simon-poole-b9a9101

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