Think of the force driving the next industrial revolution, and there comes Artificial Intelligence (AI). It is no longer the future, it is the present. AI is reshaping industries and redefining almost everything. Across the world, AI is accelerating progress, from revolutionizing healthcare to optimizing financial services. Yet, in Africa, the AI conversation is layered with complexity. While the potential of AI is undeniable, the continent faces deep-rooted challenges that threaten to leave it behind in this technological revolution.
The question is not whether AI will change Africa, it already is. The real question is: Will Africa take charge of its AI future, or will it remain a passive consumer of innovations built elsewhere?
This was the heart of The High Street Journal’s conversation with Stephanie (S.I.) Ohumu, an AI expert and Chief Analytics Officer at Point Sigma, a London-based AI company. With a Master’s degree in AI and Data Science from the University of Keele, Stephanie has been at the forefront of global AI discussions, contributing to two Emmy-nominated BBC documentaries and leading AI workshops at institutions like the London School of Economics and the MacArthur-funded TigerEye Foundation.
She painted a vivid picture of AI’s reality in Africa, where we are, where we should be, and the critical steps needed to ensure AI works for us, rather than against us.
The AI Divide: A Continent Moving at Different Speeds
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According to Stephanie, AI adoption in Africa is unfolding in two distinct realities. In industries like fintech, e-commerce, and telecommunications, AI is already driving major transformation. In Nigeria, South Africa, Kenya, and Ghana, businesses are integrating AI-powered solutions to streamline operations, detect fraud, and enhance customer experiences.
But elsewhere, in education, governance, and healthcare, AI adoption remains painfully slow. The reasons? Weak infrastructure, limited investment, and the absence of clear policy frameworks.
“If you’re looking at high-tech industries, adoption is a lot higher,” Stephanie noted. “But if you look at governance or education, it’s still very low.”
She explained that while some African nations have developed national AI strategies, many lack the structured policies and investment frameworks to implement AI on a large scale. Africa does have a somewhat unified strategy, as the African Union Executive Council endorsed the Continental AI Strategy during its 45th Ordinary Session in Accra, Ghana, on July 18-19, 2024. This strategy reaffirms Africa’s commitment to an Africa-centric, development-focused approach to AI, promoting ethical, responsible, and equitable implementation.
However, the challenge lies in the vast differences in infrastructure and resources across different countries, which create an uneven pace of adoption. While some nations are making significant progress, others risk being left behind due to these disparities.
But for Stephanie, waiting is not an option. She challenged the argument that Africa must first solve its “basic” problems before prioritizing AI.
“This is the same argument people made when mobile connectivity was introduced in Nigeria,” she said. “Yet, despite all the infrastructural challenges, Nigeria leapfrogged into a mobile-first economy. AI is no different.”
In Stephanie’s view, Africa cannot afford to put AI on hold. Progress in one area does not have to come at the expense of another.
“We cannot afford to keep focusing on pencil factories or say, ‘Oh, we need to cure malaria.’ It’s not mutually exclusive,” she asserted. “We need to think about making it easier for people to access AI urgently while also progressing in other areas.”
AI is Expensive—But Can Africa Afford to Ignore It?
For many African governments and businesses, the biggest concern surrounding AI is cost. AI is expensive, not just financially, but in every sense of the word.
“Artificial intelligence is very expensive,” Stephanie acknowledged. “You need a lot of talented engineers, a lot of data centers, and extensive data processing capabilities.”
She explained that AI development demands massive computing power, high-quality infrastructure, and highly skilled talent, resources that are often scarce across the continent. In wealthier nations, governments and corporations can allocate billions of dollars to AI research. But in many African countries, where leaders are struggling to provide basic healthcare, education, and economic opportunities, AI investments often take a backseat.
Without a clear investment strategy, AI development in Africa risks being indefinitely delayed. But Stephanie warned that failing to invest now could cost Africa far more in the long run.
“It’s not just about money,” she explained. “It’s about having the right people and the right data. AI is only as powerful as the data it learns from, and if Africa doesn’t have control over its own data, we will always be playing catch-up.”
Data is the Fuel—And Africa Doesn’t Own Enough of It
AI systems are only as good as the data they are trained on. The problem? Most AI models today are built on Western-centric datasets. These datasets often fail to capture the linguistic, cultural, and economic nuances of Africa.
“The amount of data we have is not comprehensive enough,” Stephanie pointed out. “It’s incomplete, and there’s not enough access to it. That’s one of the biggest ethical challenges—lack of inclusion.”
She also raised a major concern: the lack of documented data on African languages. AI-powered services like chatbots, voice assistants, and machine translation tools struggle to function effectively in many African countries simply because their languages are not well-represented in AI training datasets.
“Language is a major resource, but there’s not enough documented data on many African languages,” she explained. “Without that, AI remains limited in its ability to serve all of Africa’s populations.”
Without localized, high-quality data, AI solutions in Africa will remain biased, ineffective, and exclusionary. The solution? African governments, businesses, and researchers must take control of data collection and management.
The Talent Crisis: Where Are Africa’s AI Leaders?
Even if Africa solves its data problem, another major challenge looms: the lack of AI expertise.
Stephanie pointed out that AI is not just about coding, it requires a multidisciplinary approach that includes mathematics, physics, and problem-solving skills. Yet, many African educational institutions still teach traditional, outdated curricula that do not prepare students for AI-driven careers.
“AI is not just about writing code—it’s about understanding complex systems and solving problems in new ways,” she noted. “We need to change how we teach AI and data science, making it more hands-on and industry-relevant.”
She however revealed that, progress is already being made in this area. Data Science Nigeria (DSN), for instance, is working towards raising 1 million AI talents and building AI solutions to improve the quality of life for 2 billion people in emerging markets.
In Ghana, AI Ghana, a non-profit organization driven by a passionate community, is actively promoting the use of AI to solve real-world problems across Africa and beyond. These initiatives reflect the growing momentum in AI education and application, bridging the gap between theory and real-world impact.
She emphasized the need for mentorship programs, internships, and real-world AI projects to help young Africans transition from theoretical knowledge to practical application. Without these opportunities, Africa’s AI workforce will remain underdeveloped and undervalued, leaving the continent dependent on foreign expertise.
The Future of AI in Africa: Build or Be Left Behind
Stephanie sees Africa’s AI future as a race against time. The world is moving forward rapidly, and Africa must take deliberate steps to avoid being left behind.
“If we don’t control our data and build our own AI solutions, someone else will,” she cautioned. “We need to stop being passive participants and start leading the charge.”
The path forward is clear:
- Africa must localize its AI development, ensuring that datasets reflect its cultures, economies, and challenges.
- It must invest in talent development, equipping young Africans with the skills to lead AI innovation.
- Governments must step up, creating policies that encourage AI investment, protect data sovereignty, and foster collaboration between public and private sectors.
Will Africa Shape AI, or Will AI Shape Africa?
AI holds the potential to transform Africa, offering solutions in governance, healthcare, education, and economic development. But its success depends on Africa’s ability to take ownership of its AI journey.
It is not enough to adopt AI, Africa must build its own AI ecosystem. That begins with localizing data, developing a skilled workforce, and fostering innovation. The choices made today will determine Africa’s place in the future of AI.
The question according to Stephanie is no longer whether AI will shape Africa—the question is whether Africa will shape AI.
