In an interview published on April 5 by RFI, Senegalese researcher Adji Bousso Dieng, a member of the new UN international scientific panel on artificial intelligence, warns against a possible “digital colonization” of Africa. The phrase is strong, but it’s not just a slogan. It designates very concrete mechanisms: tools designed elsewhere, local data poorly represented, and economic value that often flows out of the continent.
Put more simply, the question isn’t only whether Africa will use AI. It’s under what conditions it will use it, who will set the rules of the game, and who will capture the bulk of the benefits.
What The Phrase Really Covers
When Adji Bousso Dieng speaks of “digital colonization,” she isn’t saying that every technology from outside should be suspected. She’s describing a power imbalance. Today, a large share of the models, cloud infrastructures, and technical standards used worldwide are designed and funded outside Africa, mainly in the United States and China. The continent therefore risks remaining a market, a deployment ground, or a labor reservoir, rather than a decision-making center.
This point matters to both the public and policymakers. An AI system is never neutral. It always reflects choices: which languages it understands well, which uses it prioritizes, which risks it tolerates, which data it values. When an administration, bank, hospital, or company adopts a tool designed elsewhere, it buys a service, but it also imports an implicit worldview.
The issue is therefore not theoretical. It touches very concrete matters: access to credit, quality of public services, translation, speech recognition, education, health, or content moderation. If the strategic layers of AI remain controlled off-continent, dependence ceases to be only technical. It becomes economic and political.
The warning raised by the researcher also didn’t come out of nowhere. The UN General Assembly adopted resolution 79/325 in August 2025, which set the terms for the new international scientific panel on AI. The United Nations website indicates the panel’s first plenary meeting took place on March 3, 2026. In other words, the debate about power dynamics linked to AI has now entered the most visible international forums.
Why Data Matters So Much
The second point raised by Adji Bousso Dieng concerns data. An AI learns from corpora. If those corpora mostly contain Western references, dominant languages, and institutional contexts far from African realities, the results will mechanically be less accurate. The problem isn’t only technical. What is underrepresented in the data often ends up misunderstood, poorly served, or misrepresented.
We already see this on very simple issues: accent recognition, processing low-resource languages, translation, or understanding less standardized administrative environments. An AI trained for banking, legal, or medical uses typical of wealthier economies doesn’t translate without friction. It may work, but poorly. And that poor fit ends up seeming normal if nobody corrects it.
African institutions have begun to respond to this challenge. In July 2024, the African Union approved its continental strategy on artificial intelligence, with a central idea: develop an African approach rooted in local needs, computing capacity, datasets, and training. In April 2025, the Global AI Summit in Africa held in Kigali also highlighted the need to better coordinate continental efforts, notably around common governance and a future Africa AI Council.
The signal is important, but let’s not kid ourselves. Between a continental strategy and true technological sovereignty, the gap remains huge. Research must be funded, useful corpora opened, data protected, infrastructures developed, talent retained, and actors supported who can scale. That’s where the credibility of the discourse is at stake.
The Invisible Work Behind the Most Visible Tools
The third mechanism is perhaps the most telling. AI doesn’t rely only on chips and algorithms. It also relies on human labor: annotating images, classifying texts, filtering violent content, correcting responses, testing models. This workforce is often invisible, yet indispensable.
The Kenyan case marked the global debate. In 2023, an investigation by Time magazine showed that Sama employees in Kenya had worked for OpenAI on classifying toxic content intended to make ChatGPT less dangerous. The investigation mentioned pay below two dollars an hour for some of these workers, as well as repeated exposure to highly violent texts. This case doesn’t summarize all of Africa’s digital economy, but it illustrates a reality: a continent can be integrated into the AI value chain through the hardest tasks without controlling the profits, intellectual property, or governance rules.
The phrase “digital colonization” takes on a very concrete meaning here. Africa doesn’t just provide usage and markets. It can also supply data, human compute time, and execution labor. As long as it has little influence on system design, standards setting, and value distribution, the risk of dependence remains structural.
What This Changes For Leaders And Decision Makers
For a public or private leader, the issue is not abstract. Choosing a cloud provider, an AI model, an annotation vendor, a data-sharing framework, or a speech recognition tool is already choosing a portion of future dependence. The real question isn’t: should we adopt AI? It’s: how to adopt it without giving up all negotiating power?
The answer does not lie in isolation. It’s not about cutting Africa off from global technological flows. It’s about entering them with more levers: more locally trained talent, more quality data governed locally, more research, stricter contractual requirements, greater transparency about the models used, and more coordination among states. Without this critical mass, national initiatives may remain interesting but fragile in the face of entrenched giants.
Ultimately, the value of the warning issued by Adji Bousso Dieng is to put power back at the center of the conversation. We often talk about AI as an inevitable technical advance. It is also an organization of knowledge, labor, and value. For Africa, the stake is therefore not simply entering the era of artificial intelligence. It is entering it while exerting greater influence over its uses, norms, and benefits.