Africa-Press – Botswana. To fully embrace the opportunities that will arise from AI, writes Abejide Ade-Ibijola, Africa needs to broaden its digital skills base.
Artificial Intelligence is central to global economic transformation. Africa risks being left behind not because of a lack of ideas or ambition, but because of a shortage of essential skills. Africa will have the world’s largest working-age population by the middle of the century, but the supply of people who can build and deploy Artificial Intelligence (AI) systems remains significantly lower than global demand. Across policy discussions, the focus often falls on infrastructure, regulation, or investment. However, the decisive factor for Africa’s AI readiness is the strength of its skills base.
Skills for AI in Africa
There is a tendency to assume that AI skills are reducible to the ability to code. In practice, AI requires a broad mix of competencies. These range from basic programming and data analysis to higher order skills such as model training, evaluation, cloud deployment, and developing responsible AI principles. A strong ecosystem needs people who can design products, engage with users, understand local markets, and translate technical solutions into viable ventures.
Many African universities continue to prioritise theoretical content over applied work. Students graduate with knowledge of algorithms but limited exposure to building complete AI systems or solving real problems using data. This theory heavy approach produces credentials but not capability, widening the gap between academic achievement and industry demand across Africa.
Evidence from GRIT Lab Africa
GRIT Lab Africa provides an example of what can be achieved when practical training is placed at the centre of AI education. The initiative has worked with more than 38 universities and trained over 3,000 students in programming, AI, and product development. The model is built on project-based learning and work integrated training, with an emphasis on solving for African businesses and society.
Students create products that respond to real needs, including a virtual reality courtroom (an award-winning, first immersive VR experience of a courtroom in Africa) for legal education, AI engines for environmental and social governance assessment, augmented reality learning tools, and digital platforms for corporate and investment banking operations. The outcomes are significant. All learners who reach the advanced level known as GRIT 4 have secured employment or internships.
What distinguishes GRIT Lab Africa is its deliberate link between technical training and commercial thinking. Students are encouraged to develop ideas that can be protected, scaled, and positioned for market use. This approach builds confidence, expands employability, and strengthens the innovation pipeline within participating universities.
Region patterns in a continental skills gap
Although interest in AI is growing across Africa, the distribution of skills remains uneven.
In East Africa, Kenya and Rwanda have strong digital innovation cultures but face shortages in advanced AI engineering roles.
In West Africa, vibrant tech communities in Nigeria and Ghana generate large numbers of entry level programmers yet lack access to research infrastructure and affordable cloud tools.
In Southern Africa, universities in South Africa and Namibia offer stronger formal programmes but struggle to extend high-quality training to rural and township areas.
North African countries, including Egypt, Tunisia, and Morocco, have long-established engineering traditions, but their AI ecosystems are not fully integrated with pan-African networks.
Studies by UNESCO, the African Union, and AI4D Africa highlight these patterns: Africa’s main constraint is not the absence of talent but the absence of sustained, practical training at scale.
Skills matter for development
At a time when youth unemployment is high, AI offers opportunities for new forms of work. Skills enable young people to participate in data analysis, automation, health diagnostics, language technology, financial innovation, and agricultural optimisation. Without a strong skills pipeline, these emerging industries will import expertise rather than draw from local talent.
Skills also support the creation of new businesses. Prototypes built by learners at GRIT Lab Africa and similar programmes show that African innovators can develop context specific solutions when given structured support.
Lastly, AI skills matter for public administration. Governments across Africa need data scientists and AI practitioners to strengthen service delivery, improve infrastructure planning, and handle complex administrative datasets. Without internal capacity, AI adoption will remain externally driven and less sustainable.
The role of universities, governments, and industry
Universities must reform curricula, strengthen laboratories, and invest in computer science and engineering faculties. This will aid research in training AI models, stimulate the environment for multidisciplinary partnerships between other faculties, such as humanities (who will ask good research questions on AI ethics), health (who will adapt AI for new applications). In the classroom, project-based models of teaching should be the future.
Additionally, GRIT Lab Africa has invested in training “craftsmen” and “craftswomen” who are not trained computer scientists or engineers but are keen on learning “just-enough technical skills” to contribute to the African innovation pool.
Governments can enable progress by expanding digital infrastructure, improving data policy frameworks, and supporting national AI strategies that prioritise human capital. Industry partners can provide datasets, internships, mentorship, and opportunities to test early solutions.
Programmes such as GRIT Lab Africa illustrate how these groups can work together. When universities, industry partners, and policy institutions align, the output is a stronger and more employable talent base.
A blueprint for scaling AI skills across Africa
A scalable continental strategy needs six main components:
What to teach, and who to target: Establish common foundational AI and programming skills within African higher education, while starting robotics and coding with primary and secondary schools. This must be augmented with a non-scientific curriculum for young people who are neither in school, nor employed; also, for young people whose domain of study is far from science and engineering.
Infrastructure, and communities of solvers: Build regional AI skills and innovation hubs that replicate successful models such as GRIT Lab Africa.
Work-integrated learning with AI skills: Introduce national and regional problem challenges that allow students to work with real data from banks, telecoms, and public agencies. Students should also enjoy short placements in real world settings (as interns) while they study, and they should be trusted with difficult problems to solve, under the right mentoring schemes of experts.
Commercialisation: Develop pathways for early-stage commercialisation linked to business schools, innovation hubs, venture capitalists, and impact investors.
AI for African governments and social good: Create public sector fellowships that place AI talent inside government departments to support essential services.
AI ethics and inclusion of the indigenous African context: The task ahead is to build AI systems that protect people, reflect African realities, and are governed by policies that prevent exploitation. This begins with ethical action to ensure that AI products do not reinforce inequality, misuse personal data, or deploy systems that communities cannot question or contest. It also requires deliberate linguistic inclusion, where African languages and Indigenous knowledge are intentionally integrated into model training so that AI tools recognise, serve, and empower all users, not only those represented in dominant global datasets. To make this possible, Africa must establish strong AI policies that guide how systems are created, tested, and deployed, using regulatory sandboxes, clear accountability measures, and regular impact assessments. These actions together strengthen trust, protect communities, and ensure that AI evolves in ways that honour Africa’s diverse cultural and linguistic foundations.
This blueprint can support long-term capacity building and provide a coherent structure for talent development across the continent.
If Africa is to participate meaningfully in the global AI landscape, skills must be placed at the centre of national and regional strategies. Infrastructure and policy are essential, but they cannot substitute for a capable workforce. The experience of GRIT Lab Africa shows that when young people are engaged through practical, problem-led, and innovation-oriented programmes, they build world-class solutions with relevance to African realities.
Africa’s AI future will not be shaped by imported technologies but by the strength of its own talent. A skills-driven approach is therefore the most reliable pathway for inclusive growth, youth employment, and long-term digital sovereignty.
LSE
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