A growing chorus of African technologists, academics, and policy thinkers are raising alarms about what they describe as a quiet recolonisation of the continent through artificial intelligence systems designed, built, and controlled by foreign entities. The continent is being integrated into global AI value chains in ways that mirror the raw material extraction model of the colonial era, with African data, African computational resources, and African human labour being funnelled into AI systems that will primarily benefit corporations and governments outside Africa.
The specific mechanisms of this emerging dependency are not always visible, but they are pervasive. Large language models and computer vision systems require enormous quantities of training data, and African countries, despite having relatively small formal digital economies, generate vast amounts of data through mobile phone usage, social media platforms, and the digitisation of government services. This data is routinely harvested by global technology companies, often without clear informed consent from the individuals whose information is being processed, and used to train AI systems that then get sold back to African governments and businesses at substantial cost. The value created flows overwhelmingly to Silicon Valley and to a small class of African elite with ties to the global tech industry.
The Infrastructure Dependency
The infrastructure requirements of advanced AI systems are also creating new forms of dependency. Training frontier models requires compute infrastructure that only a handful of countries and corporations can afford to build and maintain. African governments and startups seeking to develop locally relevant AI applications must rent computing capacity from the same foreign cloud providers who are competing to harvest African data. The result is a dual dependency: on data extraction and on compute infrastructure, both controlled by entities that owe no loyalty to African citizens and face no meaningful accountability to African regulators.
The Stakes Are Political, Not Merely Economic
The stakes of this debate extend far beyond economics. AI systems are increasingly embedded in decisions about who gets a loan, who gets a job, who gets healthcare, and how governments allocate resources. Systems trained on data that reflects the priorities and biases of wealthier societies may perform poorly in African contexts and systematically disadvantage African people in ways that are difficult to detect or challenge. As AI becomes embedded in the continent’s governance and economic infrastructure, the question of who controls the underlying systems will be not merely a technical question but a fundamental political one.
What African Countries Can Do
Experts argue that African governments must act now to establish data sovereignty frameworks, invest in continental compute infrastructure, and build the regulatory capacity to hold global AI companies accountable for how they use African data. Regional bodies like the African Union and the African Development Bank have roles to play in coordinating these efforts and mobilising the capital required. But the necessary actions also include building African AI talent, supporting local AI startups, and creating the kind of enabling environment that would allow the continent to move from being a subject of AI extraction to a participant in AI creation.