The 8 pillars each country should benchmark his AI maturity against!

Over the past two months, I attended two major conferences focused on AI in Africa: one organized by the London School of Economics (LSE) and the other by the Cambridge Africa Society I am always fascinated by these discussions and love seeing how brilliant minds from top universities think about the future of AI on the continent.

However, during a panel at the Cambridge conference, a moderator asked what Africa’s AI tech stack should look like. In response, the speakers immediately fell into a familiar trap: they began listing all of the continent’s problems as if Africa were one single, monolithic block. While their intentions were good, I believe this approach is conceptually flawed and reveals a fundamental misunderstanding of the African continent.

We cannot treat Africa as a monolith when debating technology. Instead, we should look at a Hierarchy of Needs for individual countries, grouping them by their technical and infrastructural maturity.

In this post, I want to outline the 8 foundational needs every country must address. For each stage, a country needs a specific level of technical maturity to implement the infrastructure, alongside a robust governance and regulatory framework to manage it.

This is not main to be a prefect post but it will help us to understand what need to be done in our countries to start thinking about Artificial Intelligence. The aim of it is to dive into each area separately and highlight success stories and lessons other african countries can learn from each other. If you country have a technical maturity don’t hesitate to let me know, I will more than happy to learn your success story.

1. Power and Electricity

A country cannot realistically discuss AI or digital sovereignty without the basics.

  • Key Questions: How reliable is the electrical grid? What is the electrification rate, and at what cost? Is it truly affordable for the less privileged?
  • Success Story: Ethiopia, for self-funding and building the Grand Ethiopian Renaissance Dam (GERD), taking ownership of its massive central power generation.

2. Internet Access

Once power is secured, we must look at connectivity.

  • Key Questions: What is the internet penetration rate? How fast and reliable is the connection? What government policies exist to regulate and expand internet access?

3. Data Centers and Digital Sovereignty

With electricity and internet established, a country can begin building actual digital infrastructure.

  • Key Questions: Where do we store our data, and who owns it? How many local data centers have we built? How are we protecting this infrastructure from cyber attacks?

4. Talent Development

We need data and internet to train local STEM experts who can implement national strategies.

  • Key Questions: How many engineers are we producing annually? How many are we sending abroad for advanced studies, and what percentage do we successfully retain? How many research papers are we producing per year? How good are we at adapting the recent research in the the STEM fields and adapt them to our needs?
  • Success Stories: There is incredible momentum here thanks to grassroots initiatives like Deep Learning Indaba and Data Science Africa, academic hubs like the African Institute for Mathematical Sciences (AIMS) (backed by Meta and Google), and the Mastercard Foundation’s massive upscaling programs.

5. Digital Government Services

A country with stable power, internet, and it own data center can finally begin digitizing its services.

  • Key Questions: How many government processes are automated end-to-end? How long does it take a citizen to get an ID card or a driving license? Can the country organize a secure election and announce verified results quickly without fraud?
  • Success Story: Rwanda’s Irembo platform, which serves as a brilliant all-in-one portal for citizen services.

6. Financial Services and Inclusion

True digital economies rely on the seamless, secure movement of money.

  • Key Questions: How easy is it to open a bank account online? Can businesses easily execute international trades and prove compliance? How efficiently can the government collect taxes digitally? What is the banking penetration rate in the country?”
  • Success Story: The widespread adoption of Mobile Money (like M-Pesa) across Africa is a masterclass in financial inclusion that we must continue to build upon.

7. Visualization and Monitoring (Data Engineering)

If a country has the previous layers in place, it should be able to track key metrics in real time. This requires strong data engineering to centralize information.

Crucial Realization: Many of our immediate problems do not actually require machine learning or sophisticated AI models. Most of them can be solved entirely by good data engineering and proper data visualization tools.

8. Machine Learning and AI

Finally, at the top of the pyramid, sits AI. This is the science of using historical data to make forecasts, automate complex systems, and drive informed decisions.

  • AI is not just Generative AI (like ChatGPT). It includes computer vision, robotics, and edge computing.
  • What this looks like at maturity: Building custom AI models trained on local African languages, deploying intelligent agents to increase public administration productivity, using computer vision to optimize traffic, or creating robotics for the agricultural and mining sectors.

Conclusion

We need to stop having generic conversations about “AI in Africa.” Instead, we should categorize African countries based on where they currently sit within this pyramid.

By mapping out where countries actually are, we can identify specific local success stories, learn how a particular nation solidified its foundation at a specific stage, and share those exact blueprints. Let’s stop visualizing AI as a single-speed race, and start discussing our varied success stories so we can learn from one another.