Sub-Saharan Africa: Why do less than 12 percent of Africans have AI access?

Reported by Laura. Originally published by Global Voices on 04 May 2026. This is an archived report; dates and circumstances refer to its original publication.

While African capitals step up their national AI strategy announcements and tech giants launch their “innovation hubs across the continent , millions of households are still living without reliable electricity . This striking paradox is central to our interview with Togolese IT specialist and internet governance and digital policy expert, Folli Herbert Amouzougan, who is also a shrewd observer of Sub-Saharan Africa’s technological dynamics.

Contrary to the enchanting narratives surrounding African “technological advances”, Folli Herbert Amouzougan asks a simple question. Given the current circumstances, can we really imagine artificial intelligence (AI) in a continent where we can’t yet guarantee electricity? Beyond algorithms, connectivity, and even data, there is a lack of electrical wiring. Based on this often-overlooked fundamental reality, he methodically debunks the prevailing optimistic tech narrative, outlining the energy, digital, economic, and linguistic divides that determine the continent’s access to AI.

In this candid interview, Folli Herbert Amouzougan questions the responsibilities of states, telecom operators, tech companies, and local civil societies.

Jean Sovon (JS): African governments and leading tech companies announce national AI strategies, innovation hubs, and partnerships with Google and Microsoft, while a large proportion of the population experiences daily power outages . How would you describe the gap between the political rhetoric surrounding AI and the basic infrastructure reality in Sub-Saharan Africa ?

I would say the gap between the political rhetoric surrounding AI and the basic infrastructure reality in Sub-Saharan Africa is untenable. I believe these pronouncements are like leaping into the unknown, and there’s no point getting ahead of ourselves. Achieving any technological feat in a country without first improving and stabilizing the energy sector and equipping it with basic infrastructure, such as an efficient and functional electricity grid that covers at least 95 percent of the country, is inconceivable to me. You cannot build a tower (AI) without a solid foundation (energy and connectivity infrastructure).

Read: A lack of electricity and internet access hinders AI adoption in Sub-Saharan Africa

JS: To what extent does the energy divide pose the primary obstacle to substantial AI adoption in this region?

FHA: Your question lays the groundwork for a better understanding of the energy divide. I often point out that there are entire African populations who typically have the same rights as you and I, but have never switched on an electric lightbulb in their lives, and die without ever experiencing electricity. Yet, using generative AI tools requires a charged device, a stable connection, and often a paid subscription. The lack of electricity access is the primary obstacle, since all AI infrastructure (whether local), interaction devices (smartphones, PCs, etc.), and means of access (SAT, internet) depend on electricity! Without electricity, there’s no internet, no operational routers, no functional telecommunications antennas, and an inability to charge smartphones.

JS: Sub-Saharan Africa is often cited as a mobile success story. However, browsing Facebook over 3G is very different from using a Large Language Model (LLM), which requires low latency and sustained bandwidth. Where exactly is the line between “ connected” and “connected for AI,” and how many people on the continent actually cross this threshold?

FHA: Generally speaking, those “connected” use 2G or 3G, or even ADSL, for social networking and have low bandwidth and high latency. Whereas those “connected for AI” use stable 4G or even 6G and full-fiber networks, which offer high bandwidth and low latency to meet the processing power requirements. The line isn’t a specific technical threshold I can give you in this answer, but a combination of criteria that must be met simultaneously. Before generative AI, “we” all (there are always exceptions) benefited from SMS/voice, mobile web, and streaming/video. However, today, the challenge is maintaining uninterrupted sessions that incorporate streaming, uploading, and real-time interactions. To that end, this line involves all aspects of the following inextricably linked criteria: bandwidth, latency, connection stability (generative AI is difficult over ADSL), device quality (old smartphones pose an obstacle), language, whether an account is required, and cost per session. It is understandable why this line is so restrictive and exclusive! Language is another key factor: the average well-off, well-equipped user from back home, who only speaks Guin (a language spoken in southern Togo), will encounter a Large Language Model (LLM) tool that doesn’t understand their language register. There can be no dialogue or communication when one’s register is different from another’s. The line, therefore, isn’t a straight path, but an interconnected filtering system. What we must remember in the African context is that this line is simultaneously technical, economic, and linguistic.

I would say the percentage of Africans actually crossing this threshold today is less than 12 percent, given all the criteria they must meet to do so. It will be extremely challenging to find 2 in 10 people.

JS: In response to the outages and data costs , adaptations such as offline use, lightweight models, embedded AI on devices, and access via feature phones are emerging. Do these seem like sustainable or stopgap solutions to you that don’t address the problem’s structural causes ?

FHA: Sustainable or stopgap solutions, it all depends on the approach taken, and especially the aim. First, we must recognize that sustainability depends on the organization funding these adaptations and the intended benefits. Within the scope of progressive initiatives, locally tailored approaches bring added value to their targets in sectors such as education, agriculture, and health, without depending on nonexistent infrastructure. However, the danger lies in AI having reduced capabilities for those less fortunate, while those better connected benefit from its full capabilities and more powerful usage. This underscores the second-tier access. The current state of affairs neither enables nor compels governments that don’t adopt progressive approaches to address the structural causes.

JS: Who’s responsible for making AI accessible in Sub-Saharan Africa, and what practical measures do you expect from each stakeholder?

FHA: Broadly speaking, responsibility is shared, which effectively enables each stakeholder to shift the blame and accuse one another, maintaining the status quo. In reality, states have full responsibility for electrification, regulations, and industries. Telecom operators keep data tariffs high in low-competition markets. Togo is the perfect example, with only two mobile phone operators that would benefit from investing in rural infrastructure. They are responsible for network accessibility through high-availability mechanisms, while AI companies are responsible for adapting their technologies. For example, they could invest in multilingual models and develop partnerships with local stakeholders who understand the challenges and can communicate the usage constraints, rather than signing superficial “hub agreements” with governments that would only benefit the minority: the elite and expats. Local stakeholders must continue to innovate in accordance with on-the-ground realities and contexts, offering SMART solutions to real-world problems.

Image credit

Cover context image: Central accra-2. This archival or illustrative image is not presented as a photograph of the reported event. Creator: Guido Sohne. Original image and full attribution. License: CC BY-SA 2.0. Resized and compressed for web display; the image retains its stated license.

Publication credits

Written (Français) by Jean Sovon Translated (English) by Laura. Original report published by Global Voices. Republished under Creative Commons Attribution 3.0. Adapted for Gistmax: formatting simplified; duplicate original-language quotations and embedded media omitted; cover photograph replaced. This republication does not imply endorsement of Gistmax by the author or publisher.