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Introduction:
At the Gates Foundation’s Goalkeepers event held in Lagos, Nigeria, the conversation around artificial intelligence (AI) took a powerful turn toward Africa’s future. One of the most compelling voices was that of Bayo Adekanmbi, CEO of Data Science Nigeria, who passionately advocated for the development of indigenous AI systems. His core message was clear: AI must be shaped by the people it serves. For Africa, this means creating technology built on local data, guided by cultural nuance, and driven by the continent’s own talent. With the digital world rapidly evolving, Adekanmbi’s vision highlights both the risks of technological dependency and the immense potential of homegrown innovation.
Africa Needs Its Own AI: An Urgent Appeal for Localized Intelligence
Bayo Adekanmbi, leading the conversation on AI’s role in Africa, emphasized that technology should never be detached from the people it aims to serve. Speaking at the high-profile Goalkeepers event by the Bill & Melinda Gates Foundation, he highlighted how Africa must move away from depending on imported AI models and datasets that do not reflect its unique realities. According to him, AI is fundamentally about understanding people—their language, culture, and societal norms. Without this, even the most advanced systems will fail to provide relevant solutions. A critical issue he raised is the underrepresentation of African languages and cultural data in today’s leading AI systems. Over 95% of African languages remain undigitized, resulting in poor performance of global AI models on the continent.
Adekanmbi illustrated the importance of diverse training data with the example of disease prediction. AI, he said, needs access to varied, unbiased datasets to function accurately in real-world situations. When it’s trained on non-representative data, it simply doesn’t work for African populations. He warned that this lack of inclusivity could perpetuate systemic biases and worsen inequalities in healthcare, education, and economic participation.
In a compelling metaphor, he drew from Nigerian proverbs to argue for local ownership: “You cannot shave a man’s head in his absence.” This, he said, applies directly to AI. Solutions for African people must involve African people at every stage—from data collection to product deployment. He also pointed to progress being made, including speech data projects for Nigerian languages supported by the Gates Foundation. The emerging talent across Africa is driving innovation, but more is needed in terms of infrastructure, policy support, and community-driven efforts.
Digital illiteracy remains a hurdle, but Adekanmbi proposed an alternative approach: adapt what already exists. He praised mobility data usage in areas lacking traditional demographics and called for a mindset shift—from complaining about what’s broken to focusing on what’s working and scaling it. The AI conversation, in his view, must move beyond dependency and into an era of African-created, Africa-centric solutions. This is not just about tech—it’s about sovereignty, sustainability, and social transformation.
What Undercode Say:
The article reveals a crucial pivot in the global conversation about AI: the call for inclusive and contextualized systems, especially for Africa. It brings attention to a deep-rooted issue in modern tech development—most advanced AI tools are built in and for the Global North, often ignoring the needs, nuances, and diversity of regions like Africa. By relying on datasets and structures developed abroad, African countries risk importing not just tools but the cultural, ethical, and systemic biases embedded in them.
Adekanmbi’s insight that “AI is about people” is both philosophical and practical. AI cannot function without training data, and that data must reflect the world it serves. Africa’s exclusion from global datasets doesn’t just result in lower performance of AI tools—it makes them fundamentally unsuitable for local problems. Take healthcare, for instance. Disease models trained on European or American patients will miss patterns specific to African populations, leading to diagnostic errors or poor treatment plans. This is not a trivial issue; it’s a matter of life and death.
Moreover, the lack of digitized African languages limits the reach and effectiveness of NLP (natural language processing) models. Chatbots, virtual assistants, and translation tools fail when confronted with African dialects, leaving millions without access to the AI revolution. Digitizing these languages is not just about preserving heritage—it’s about empowering participation in the digital economy.
The metaphor about shaving a man’s head in his absence is a cultural bombshell in this context. It’s a powerful way to say: nothing about us without us. Africa’s participation in the AI era must be full and central, not peripheral. This means investment in local education, AI research hubs, community-led data collection, and linguistic digitization projects.
His comments on adaptive innovation—using what’s available rather than waiting for perfect conditions—are vital for any under-resourced region. For example, using telecom data to map population movements in rural areas is a brilliant workaround when census data is lacking. This approach is not just practical—it’s visionary. It embodies a resilient, proactive spirit that can redefine Africa’s digital future.
Another layer to the analysis is the role of global institutions. The Gates Foundation supporting speech data development for Nigerian languages shows that collaboration is possible and beneficial. However, it must always come with respect for local leadership. Foreign help must not become foreign control.
Finally, Adekanmbi’s optimism is infectious. He believes that Africa has the talent and energy to lead its own AI revolution—and the seeds are already being planted. The ecosystem is forming, and the momentum is real. His call is not a complaint but a challenge: let’s build AI that understands us, speaks our languages, solves our problems, and reflects our values. The future belongs to those who code it.
Fact Checker Results:
✅ The claim that over 95% of African languages are not digitized is accurate
✅ AI systems perform poorly in African contexts due to lack of local data
✅ Projects digitizing African languages, including those funded by Gates Foundation, are underway 🎯
Prediction:
As Africa continues investing in local AI talent and infrastructure, we’re likely to see a rise in indigenous AI startups and solutions tailored to African challenges. Within the next five years, more than 30% of new African tech ventures could be AI-driven, with increasing global partnerships centered around ethical data collection, linguistic digitization, and cultural preservation through machine learning. 🌍🤖📈
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Reported By: www.channelstv.com
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