Cooperating to Advance Africa-Centric Education in the Age of Artificial Intelligence and Intellectual Property: Lessons from the African Continental Artificial Intelligence Strategy 2024

In this blog post, Susan Isiko Štrba considers digital inequalities and how the Global South might respond in the AI moment. 

Sustainable Development Goal 17 highlights the importance of public–private partnerships (PPPs). In an earlier blog, I explored how partnerships in the field of intellectual property (IP) can improve access to educational materials for visually impaired persons. I looked at two international initiatives that help expand access to published works for people who are blind, visually impaired, or otherwise print-disabled.

In this blog, I want to focus on another area where cooperation is urgently needed: artificial intelligence (AI) and education in Africa. I argue that policymakers, educational institutions, local AI developers[1], and private-sector actors across the continent should work together to build AI systems that reflect African educational priorities, cultures, and realities. Although the data used to train AI systems may be protected by intellectual property rights, IP can also be managed in ways that support innovation, education, and local development.

Drawing from the African Union Continental Artificial Intelligence Strategy 2024, I suggest that African countries should cooperate to regulate, finance, and develop Africa-centric AI models. I also use BharatGen as a comparative example to show that locally financed and locally grounded AI development is both possible and valuable.

Education in the African Union AI Strategy 2024

AI is already changing education around the world. Personalized learning platforms, virtual assistants, and automated assessment tools are reshaping how students learn and how teachers teach. These technologies create real opportunities to improve both the quality and accessibility of education.

At the same time, the rapid expansion of AI in higher education raises important concerns. If introduced without proper safeguards, AI systems could allow commercial interests to shape public education and weaken academic independence.[2] Policymakers therefore need to strike a careful balance between using AI to expand educational opportunities and protecting students, institutions, and cultural identity.[3]

UNESCO’s ethical guidelines on AI call on governments to establish legal and institutional frameworks that ensure AI serves the public good. The African Union AI Strategy is an important step in this direction. The strategy promotes a people-centred, inclusive, and development-oriented approach to AI governance. One of its priorities is strengthening regional and international cooperation to build national and regional AI capabilities and improve Africa’s position globally.

Two action areas in particular stand out to me. The eighth action area focuses on developing AI skills and talent in schools, universities, workplaces, and across society more broadly, including reskilling workers whose jobs may be affected by automation. The thirteenth emphasizes coordination among academia, civil society, governments, the media, and the private sector to maximize AI’s benefits while reducing its risks. Read together, these two action areas point toward a cooperative and human-centred approach to AI development in Africa.

Education—alongside health and agriculture—is identified as a priority sector in the Strategy. The document encourages investment in digital infrastructure, training, startups, and innovation hubs, while also calling for policy frameworks developed through broad stakeholder consultation.

Promoting Local Tech Companies for Africa-Centric Education

Many African countries, like others in the Global South, still lack the infrastructure needed to develop large-scale AI systems. As a result, much of the training data, computing power, and underlying technology remains controlled by large foreign technology companies such as Google and Microsoft. At the same time, AI systems are often built on invisible and underpaid labour in developing countries. In Kenya, for example, thousands of workers perform “ghost work” to help train AI systems behind the scenes.

If Africa wants AI systems that genuinely reflect its languages, cultures, and educational priorities, the continent must reduce its dependence on foreign datasets and external technological control. Encouragingly, there are already signs of progress. Nvidia, for instance, is partnering with Cassava Technologies to build Africa’s first AI factory, a major supercomputing project that would allow local AI training without exporting African data abroad.

I believe AI could play a transformative role in expanding access to education across Africa. AI-powered platforms could help reach students in remote regions, provide personalized learning experiences, and improve educational quality where resources are limited. Localized AI tutor applications that work offline or with minimal internet access could become especially important in addressing infrastructure challenges and educational inequality.

However, realizing this potential requires educational institutions to integrate AI and digital technologies into their curricula. Students need opportunities to develop the technical and critical skills necessary for an AI-driven world. This will require strong collaboration among governments, universities, and the private sector—particularly local technology startups. Such partnerships can support training programs, strengthen technical capacity, and create an enabling environment for emerging African AI companies.

Policy Considerations

In my view, African countries should prioritize partnerships among themselves rather than relying primarily on collaborations with Western technology firms. Where foreign companies are involved, governments should lead the partnerships and clearly define the terms of cooperation.

Data governance must remain central to these arrangements. African governments should seek to retain ownership and control over national data and databases. One possible approach would be to offer tax incentives or tax holidays in exchange for shared ownership or access rights to locally generated datasets. If major technology companies reject such conditions, governments may need to invest directly in domestic AI development while establishing strong regulatory frameworks for educational institutions.

Local datasets are far more likely to reflect African languages, cultures, and social realities. Although many African countries still use colonial languages in schools and formal institutions, initiatives such as Masakhane are already working to develop datasets for African languages despite the continent’s immense linguistic diversity.

For this reason, I believe Africa should not simply build applications on top of existing global AI systems. The continent should also invest in developing its own Africa-centric AI models. Doing so would strengthen inclusivity, improve cultural relevance, and reduce some intellectual-property challenges. But this effort cannot rest on governments alone. It requires collaboration among governments, international organizations, universities, linguists, local communities, and the private sector.

The databases created through these efforts should ideally be owned by African institutions, which should also hold the associated copyright. Too often, Africans generate and label the data used to train AI systems while ownership of the databases remains concentrated in large technology companies. Control over those databases ultimately determines who can access and benefit from the data. When African institutions generate and manage their own datasets, many IP concerns become easier to address.

I also believe educational institutions should adopt more flexible academic policies. Evaluation systems should not rely exclusively on publications in closed-access journals. Greater recognition of open-access publications and self-published online research would encourage wider knowledge sharing and make African scholarship more visible and accessible to AI systems through web crawlers and digital repositories.

Of course, all of this requires funding. At present, much of the available financing for AI research and development comes from large foreign technology companies. Unsurprisingly, this influences research priorities, the types of data collected, and the structure of educational programs. If Africa wants AI systems that truly reflect its own priorities and realities, the continent must invest in its own AI ecosystem—and that will require continental cooperation.

Cooperation for Resource Mobilization

The idea that African governments should finance AI development themselves may sound ambitious, but it is not unrealistic. Some developing countries have already taken this path.

India’s BharatGen initiative offers an interesting example. BharatGen is a government-funded generative AI project designed specifically for India’s multilingual and multicultural context. Using India-specific datasets, it supports multilingual and multimodal AI systems capable of generating high-quality text and speech across many Indian languages. It also provides an open-source platform for startups, researchers, and developers while promoting data sovereignty and cultural relevance.

What I find particularly important about BharatGen is that it aligns AI development with broader goals of technological self-reliance, linguistic diversity, cultural preservation, and social inclusion. It shows how public investment can shape AI systems around local priorities rather than external commercial interests.

Africa could pursue a similar path through regional cooperation and pooled resources. Governments could jointly finance continental AI initiatives, while educational institutions collaborate on research and capacity building. The challenges are significant, but they are not insurmountable.

Africa already possesses one of its greatest strengths: a young and technologically engaged population. By focusing on AI solutions that serve the public interest rather than trying to compete directly with global technology giants, the continent can build systems that respond to local educational and social realities. In doing so, education in Africa would not simply be shaped by technology, but guided by African values, cultures, and priorities.

References

African Union (2024). Continental Artificial Intelligence Strategy: Harnessing AI for Development and Prosperity.

Agwaibor, S. (2026). “African’s AI Builders: 207 Startups and one Continent’s Bet”, Techcabal Insights. https://insights.techcabal.com/africas-ai-builders-207-startups-and-one-continents-bet/

Batia, T. (2014). “India Launches BaratGen, a Groundbreaking Multimodal Generative AI Project”, JustAI. https://justai.in/india-launches-bharatgen-a-groundbreaking-multimodal-generative-ai-project-08-10-24/

Chair, C. (2026). “Linguistic Diversity”, AI Now, Institute.  https://ainowinstitute.org/publications/linguistic-diversity.

Dosunmu, D. (2025). “What you need to know about Africa’s first AI factory”, Rest of the World Reporting Global Tech Stories”,  https://restofworld.org/2025/nvidia-africa-ai-factory/.

Dosunmu, D. (2025a) “Big Tech’s “AI for good” spending increases in Africa. So does skepticism”. Rest of the World: Reporting Global Tech Stories. https://restofworld.org/2025/africa-ai-for-good-big-tech/.

Faul, M. V. (Ed.). (2024). AI and Digital Inequities. Policy Insights, Norrag.

Korir, K. (2025). “The Linguistic Diversity of Africa: A Treasure at Risk and the Role of AI in Preservation”, https://www.linkedin.com/pulse/linguistic-diversity-africa-treasure-risk-role-ai-kiplangat-korir-t4v2f/.

Kuwonu, F. (2025). “AI and the future of learning”, United Nations. https://africarenewal.un.org/en/magazine/ai-and-future-learning

UNESCO. (2026). Global AI Ethics and Governance. https://www.unesco.org/en/artificial-intelligence/recommendation-ethics.

Wegemer, C. (2025). “Why higher ed’s AI rush could put corporate interests over public service and independence”, The Conversation” https://theconversation.com/why-higher-eds-ai-rush-could-put-corporate-interests-over-public-service-and-independence-260902

Williams, J. (2026). “Book review: Code Dependent, by Madhumita Murgia”, Earthbound, https://earthbound.report/2026/02/12/book-review-code-dependent-by-madhumita-murgia/.

Author

Susan Isiko Štrba is Counsel and Senior Fellow at the Centre on Knowledge Governance. Her research focuses on the intersection of cooperation, intellectual property, and artificial intelligence in Africa.

susan.isikostrba@graduateinstitute.ch

[1]There are currently over 207 AI Startups in Africa, 14 of which are in the field of education, with the startups in the education sector recording the fastest growth between 2022 and 2025. See, Stephen Agwaibor, “African’s AI Builders: 207 Startups and one Continent’s Bet”,  Techcabal Insights. 1 April 2026 https://insights.techcabal.com/africas-ai-builders-207-startups-and-one-continents-bet/

[2]Chris Wegemer. (2025) “Why higher ed’s AI rush could put corporate interests over public service and independence”, The Conversation” https://theconversation.com/why-higher-eds-ai-rush-could-put-corporate-interests-over-public-service-and-independence-260902

[3]For a detailed discussion, see Faul, M. V. (Ed.). (2024). AI and Digital Inequities.