Framing the AI Challenge in Africa
Africa’s digital landscape remains uneven, with many systems still manual or paper-based, highlighting deep technological gaps. Meanwhile, global discourse about generative AI’s transformative power grows louder and faster.
Yet internet access in Africa lags significantly behind global averages, limiting both participation and economic inclusion. Moreover, Africa has less than one percent of global data center infrastructure and AI research output. Thus, urgent questions arise about timing, preparation, and strategic integration of AI technologies.
The Core Argument: Sequence Before Speed
The central idea asserts that premature AI adoption poses risks when underlying digital systems remain weak. This mirrors past development lessons where early industrial investment failed without shilled labor or supply networks. Without sequencing, Africa risks automation that displaces labor before new opportunities emerge.
Importantly, the region’s young workforce could be harmed by technologies that bypass workforce development. Therefore, timing matters as such as adoption itself in shaping long-term productivity gains.
Understanding the Digital Dependency Risk
If adoption outpaces preparation, Africa could become a digital raw data exporter rather than an AI value creator. This would replicate historical extractive patterns now applied to data instead of minerals.
Without local digital foundations, AI algorithms, platforms, and governance systems will be designed externally. Consequently, Africa could remain a consumer of digital products, not a contributor to innovation. This scenario intensifies dependency on foreign technology and erodes digital sovereignty.
Four Sequencing Priorities
First, Africa should assert control over its data ecosystems, shaping digital industrial policy. Robust frameworks can mandate data ownership, interoperability, and local analysis capacity. Where countries govern data effectively, they wield greater influence over AI value creation.
Next, essential digital infrastructure like e-payments, digital IDs, and data centers must be expanded. These foundations act like roads or power grids did in earlier industrial eras. When Africa strengthens these layers, AI tools have a viable platform to operate on.
In addition, controlled deployment using pilots and feedback loops helps manage disruption. Gradual integration ensures training on local data and tailoring to contextual needs. This measured approach minimizes negative impacts on markets and labor.
Finally, Africa can learn from others’ mistakes, setting new governance and inclusion benchmarks. Examples from digital payment innovations show how late entrants can still lead globally. Strategic sequencing thus becomes not delay, but competitive positioning.
Why Sequencing Matters for Inclusion
If AI deployment aligns with local contexts, Africans can benefit economically and socially. Otherwise, rapid AI adoption could worsen inequality and displace workers prematurely. Sequencing allows digital transformation to precede automation, balancing innovation with societal needs. Consequently, Africa can cultivate its own ecosystems instead of importing finished systems.
Strategic and Sovereign Integration
AI should not be resisted, but prepared for with intention and capacity building. Sequenced AI adoption aligns technological change with economic and human development priorities.
In this way, Africa can avoid repeating dependency cycles of past eras. Deliberate sequencing helps ensure shared prosperity, not disruptive displacement. Thus, Africa’s goal becomes shaping its digital future on its own terms.
Source:
Doumba, M.-A. (2026, 10 de febrero). Why Africa should sequence, not rush into AI. Brookings Institution. https://www.brookings.edu/articles/why-africa-should-sequence-not-rush-into-ai/