During the Global AI Summit on Africa held in Kigali in April, experts pointed out that by 2030, AI could add $19.9 trillion to the global economy, with Africa’s share estimated at $2.9 trillion.
This windfall could lift 11 million Africans out of poverty and create half a million jobs annually. However, beneath this optimism lies the sobering question of Africa’s real place in this ecosystem.
Africa is one of the world’s largest producers of data, the oxygen that fuels the AI economy.
We must therefore ask ourselves this: If our data powers billion-dollar industries elsewhere, are we shaping the algorithms of tomorrow, or simply supplying raw material for others to profit from? Every mobile transaction, health record, satellite image, and social media post across the continent feeds vast datasets.
Unfortunately, the algorithms built on this data are rarely designed for African realities, whether in healthcare, language, or socio-economic development.
Driven by the world's youngest and mobile-connected population, Africa is an unparalleled source of real-time digital information.
According to DataReportal’s Global Digital Report, Kenya now ranks as the world’s leading ChatGPT user, with 42.1 percent of users aged 16 and above actively engaging with the tool.
South Africa follows closely at eighth worldwide, with 34.3 percent of active users. Yet generative AI tools seldom reflect our needs. In healthcare particularly, diagnostic systems trained on Western datasets may be effective in those contexts but often fall short in Africa, where conditions such as sickle cell disease, malaria, and maternal health challenges are widespread.
The same applies to language. Although Africa is home to more than a quarter of the world’s languages, most remain absent from AI systems.
Tools like ChatGPT or DeepSeek are overwhelmingly trained on English, Chinese, and European languages, excluding millions of Africans from the benefits AI promises. While our data trains the world’s AI, the tools we get in return are ill-equipped to handle our languages and cultures, or to solve our problems.
Exclusion is not the only risk. Dependency is an even greater danger. Just as Africa once exported raw materials only to import expensive finished products, today we risk exporting raw data and importing costly, ill-fitting AI systems built elsewhere. This vulnerability is not just theoretical.
When USAid ended health programmes in Kenya such as the Kenya Demographic Health Information System, the Kenya Master Health Facility List, and Kenya Electronic Medical Record system, access to critical platforms was lost.
These tools, central to disease surveillance and vaccine tracking, were hosted on foreign servers. While such systems were undeniably useful, the dependency they created highlights the threat to Africa’s digital sovereignty.
In today’s world, data is the new resource, and algorithms are the machinery of power. Without control over either, Africa risks being locked into a subordinate position in the global digital hierarchy.
The path forward must be different. Africa must assert its data sovereignty, ensuring that data generated within its borders is governed, protected, and used to serve African priorities.
Investment in local research and digital infrastructure is equally critical, supporting universities, startups, and innovation hubs to develop AI solutions tailored to our contexts.
Encouragingly, some examples already exist. In East, West, and Southern Africa, M-Kopa’s AI-powered smartphones use mobile payment data to generate credit scores, helping low-income users access smartphones through micro-payments.
In Nigeria and the United States, CDIAL’s Indigenius AI supports more than 180 African languages with conversational AI, speech recognition, translation, and chatbot tools, bridging digital access for millions.
However, individual innovations will not be enough. A fragmented approach will only deepen dependency, while collective strategies can amplify bargaining power and foster cross-border innovation.
Beyond that, Africa must seize the chance to build culturally intelligent AI. Current global tools still struggle to understand African experiences, producing biased or stereotypical results.
This is our opportunity to design frameworks that reflect our realities, cultures, and aspirations and in the process, reshape the global AI landscape.
The question, therefore, is not whether Africa will be part of the AI revolution, but how. To shape this future, the continent must invest in robust digital infrastructure, develop a skilled AI workforce, and establish governance frameworks that balance innovation with privacy and security. Our goal must be to maximize opportunities while minimising external dependencies.
Ultimately, the algorithms of tomorrow will shape health, education, trade, and culture for generations.
Prof Lukoye Atwoli is the Dean, Aga Khan University, Medical College, East Africa
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