Enzi president: Africa’s AI future depends on slashing inference costs

Oji Udezue, president of Enzi, has argued that reducing the cost of AI inference is critical to making artificial intelligence accessible and practical for Africa. In an interview with TechCabal, he emphasized that the continent’s ability to benefit from AI hinges on affordability, local language support, and economic viability—not just model performance.

Tarun Mottlia

Editor, Lazyfounder

Published Nov 2, 20262 min read

Enzi president: Africa’s AI future depends on slashing inference costs — Image: TechCabal via source

Why AI inference costs matter for Africa

Oji Udezue, president of Enzi, told TechCabal that Africa’s ability to benefit from artificial intelligence depends on reducing the cost of AI inference—the expense incurred each time an AI model generates a response or performs a task. Unlike the one-time cost of building models, inference costs recur with every use, directly impacting whether AI applications remain affordable for businesses and individuals across the continent.

Affordability as a barrier to adoption

Udezue highlighted a gap between the cost of using AI and the earnings of many Africans, warning that access means little if people cannot afford consistent use. For AI to become viable in Africa, models must work in local languages and address the specific circumstances of users, not just rely on connectivity or computing resources.

The World Bank’s Digital Progress and Trends Report 2025 frames affordability as part of a broader infrastructure challenge, alongside connectivity, computing resources, locally relevant data, and digital skills. Without lower inference costs, even promising AI applications may fail to gain traction in everyday use.

A shift from model power to economic viability

Udezue emphasized that the future of AI hinges on inference economics, not just building more powerful models. He quoted, "The future of AI really goes through inference," pointing to the need for AI tools that are practical and cost-effective enough to support routine work across diverse markets, including Africa and the U.S.

Lower inference costs could make AI applications commercially practical for businesses, particularly in regions where affordability is a constraint. Udezue’s approach includes demonstrating what developers can achieve with cheaper AI tools, pivoting the conversation from theoretical potential to tangible value.

What this means

Lazyfounder analysis — our interpretation, not reported fact.

Udezue’s argument reframes AI adoption in Africa as an economic challenge rather than a technical one. For founders and operators, this signals a shift in priorities: scaling AI in low-income markets may require optimizing for cost-efficiency and local relevance over raw model performance. It also underscores the risk of assuming that global AI tools, designed for wealthier markets, will translate seamlessly to Africa without addressing affordability or language barriers.

Sources

TechCabal · 2026-10-30
Africa needs cheaper AI to reap economic gains, says Enzi’s Udezue

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