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Yinka’s view This month, Togo invited citizens to contribute texts, recordings, and translations to help AI models understand the West African country’s 50 local languages. The absence of African languages from large language models has become a major concern for the continent’s policymakers and tech leaders. But initiatives like Togo’s suggest the future of AI in Africa may hinge less on who builds the biggest model than on who makes the technology useful to the most people. Global AI investment is expected to hit $2 trillion this year, according to research firm Gartner, as tech giants race to build computing power and infrastructure. But few African companies are capturing the cloud computing spending, and even then the numbers are tiny: Africa has 18% of the world’s population, but only 0.6% of global data-center capacity, the World Bank says — and just 5% of that is equipped for advanced AI workloads. For now, the continent’s main link to the boom is demand for minerals such as copper and cobalt. The bigger prize is productivity, from how farmers reach markets to how governments deliver services. The African Development Bank estimates inclusive AI adoption could add up to $1 trillion to Africa’s GDP by 2035. But without the infrastructure and energy to deploy it, AI is unlikely to add meaningfully to growth. That’s why the World Bank argues in its biannual Economic Update, published this week, that most African economies should adopt and adapt AI rather than build frontier models from scratch — an expensive use of limited resources. Togo shows what adaptation looks like: A model that can’t understand citizens’ languages is of little use in delivering government services. African countries don’t need to win the race to build the biggest model, but they do need to make AI productive across their economies. They also can’t afford to merely be suppliers to the AI revolution or just consumers of finished AI products; they need to become places where that revolution delivers its biggest gains. Notable - The World Bank highlighted several low-cost but impactful uses of AI in Africa: Tools that support student learning, help farmers detect and manage livestock diseases, and automate tasks such as accounting for small businesses.
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