IN the words of an African proverb, “Until the lion learns to write, every story will glorify the hunter”.
Africa must write its own artificial intelligence (AI) story — one of empowerment, equity, and innovation. By asserting its role not just as a source of data but as a decision-maker, Africa will not only shape the future of AI, but also secure a more just and inclusive future for all.
Our continent’s 1,4 billion people are both the backbone of the AI revolution and at risk of being sidelined by it. In the world of artificial intelligence, data is the new oil, and Africa is a vast reservoir.
Every day, Africans generate vast amounts of data — from smartphone usage in Lagos to mobile money transactions in Nairobi and social media engagement in Cairo.
This data encapsulates a rich tapestry of languages, cultures, and experiences, making Africa a crucial contributor to AI’s diversity. If AI is to work for everyone, it must learn from African voices, faces, and narratives.
Yet, merely supplying data is not the same as having a seat at the table. Africa’s role in AI is often limited to feeding information into systems without sufficient influence over how these technologies are developed or deployed.
Our people’s images, speech, and digital interactions help train AI, but who is setting the terms? This question is fundamental to whether AI will empower Africans or perpetuate historical inequities.
AI mirrors the data it is fed and the people who build it. Without intentional efforts toward diversity, AI systems risk reinforcing harmful biases.
- Time running out for SA-based Zimbos
- Sally Mugabe renal unit disappears
- Epworth eyes town status
- Commodity price boom buoys GB
Keep Reading
We have already seen troubling examples: facial recognition software that fails to identify dark-skinned faces, voice assistants that struggle with African accents, and algorithms that disproportionately associate Africa with poverty and conflict due to biased training content. These are not mere glitches; they have tangible consequences on opportunities and livelihoods.
Consider an AI-driven hiring tool that unwittingly filters out CVs with African-sounding names or a medical AI system trained on Western datasets that fails to detect diseases prevalent in African communities.
When AI does not recognise or respect African contexts, the outcomes range from frustrating to life-threatening. The core issue is that many AI models are developed without African oversight. If the teams building these systems lack African representation, blind spots are inevitable.
Ensuring AI serves Africa is not just an act of goodwill; it strengthens AI for everyone. A system trained to understand a Nigerian farmer’s accent or a Kenyan teacher’s dialect will perform better across diverse global populations.
To achieve this, AI development must prioritise fairness and inclusivity from the outset — from data collection to model training and testing.
Bias is not an immutable flaw; it can be addressed, but only through intentional, corrective action. Africa’s vast diversity is an asset that can help AI evolve into a truly global technology.
Historically, Africa has too often been seen as a source of raw materials rather than a creator of finished products — whether it was gold, oil, or coffee.
We must not let data become the latest resource extracted without benefit to Africans. There is a growing concern that the AI boom could turn into digital colonialism: a scenario where foreign tech companies harvest African data and talent to fuel their algorithms, with minimal local involvement or reward.
The parallels are stark. Multinational tech firms set up data centres or AI hubs on African soil, but who owns the insights and profits that result?
If vast amounts of African-generated data are stored on servers in Silicon Valley or Europe, Africa loses control over that digital treasure.
Who owns the data, owns the future in the AI age. Without proper safeguards, we risk a future where Africa is merely the dataset for AI models developed elsewhere — essentially, the world’s AI supplier, but not an equal consumer or innovator.
This dynamic is already visible. Consider the unseen armies of young Africans employed to label images or moderate content for AI systems, often for very low pay.
Their work makes AI smarter and safer for the world, but they remain invisible in the value chain. Meanwhile, AI solutions built abroad are sold back to African governments and companies as pricey imports.
This imbalance echoes the old extractive economies, and it is one we have the power to change. Africa can — and must — push back at being cast only as a data provider.
Our data and our people’s contributions are valuable; we should negotiate from that strength. That means insisting on fairness: if our data is used, it should be with our permission, under our governance, and ideally processed on our soil to create local jobs.
It also means being cautious about adopting AI systems developed without our input — a one-size-fits-all tool from abroad might carry biases or assumptions that do not fit our needs.
To avoid being just a footnote in the AI revolution, Africa needs strong governance and ethical representation in all things AI. This starts with policy. We are seeing encouraging moves by some African governments and the African Union to outline AI strategies that emphasise data sovereignty, privacy, and accountability.
Such policies are crucial. They can mandate, for example, that sensitive African data stays within the continent, or that AI products be tested for bias before deployment.
When African regulators set their own standards, tech companies must respect local norms and rights rather than imposing outside standards by default.
Equally important is Africa’s voice in the global conversation about AI ethics and governance. Internationally, guidelines and frameworks for AI are being drafted — Africa should be present and heard.
We have unique perspectives on community, equity, and justice that can enrich global AI principles. For instance, how AI might affect communal societies in Africa, or our concepts of fairness, could broaden the typically Western-centric debate on AI ethics. If Africans are not at the table, there is a risk that global AI norms will be shaped without considering one-fifth of humanity.
Ethical representation also means having Africans in the rooms where AI is designed — not just as token participants, but as decision-makers. From corporate AI ethics boards to research conferences, African experts (including women and other underrepresented groups within Africa) should be actively involved.
This diversity in decision-making is not just about justice; it leads to better AI outcomes. An African engineer or social scientist can spot cultural blind spots or raise questions others might miss.
A governance mindset rooted in local context will ask: “How will this AI impact a rural clinic in Uganda? Is this chatbot equally useful for a user in Ghana who speaks Twi or a Nigerian who converses in Pidgin English?”
These questions might never occur to a developer in London or San Francisco.
By embedding ethical representation at every level — from local town halls discussing facial recognition in public security, all the way up to the United Nations (UN) forums on AI — we ensure AI develops in a way that respects African values and realities.
Perhaps the most exciting frontier is the rise of indigenous AI research and innovation in Africa. The continent is brimming with tech talent and entrepreneurial energy.
Across African cities, startups and research labs are beginning to build AI solutions tailored to local challenges. From using machine learning to improve crop yields in drought-prone regions, to natural language processing that understands Kiswahili, Yoruba, or Amharic — these homegrown innovations show why investment in African AI is so vital. Who better to design solutions for African problems than African innovators?
To truly shape AI, Africa needs to invest aggressively in its human capital and research infrastructure. This means more funding for universities to establish AI and data science programmes, and scholarships to train the next generation of AI engineers and ethicists.
It means creating incentives for our talented software developers and data scientists to stay and work on the continent, rather than being lured overseas. We already have examples to build on: institutes and programmes focused on AI in Africa are emerging, and pan-African collaborations (such as networks for AI researchers in different countries) are fostering knowledge exchange.
International partnerships can help, but they must be partnerships of equals, with African institutions leading the way in setting research agendas.
Local investment is equally important. African governments and businesses should view funding AI not as a luxury, but as a necessity akin to building roads or power lines.
AI will underpin industries from agriculture to banking to healthcare; investing in our own AI capabilities will pay off in economic growth and improved services.
Imagine if every major African university had an AI centre producing innovations for community health or local languages, or if every African nation set aside a fund for AI startups solving local issues. These efforts create an ecosystem where indigenous AI flourishes.
Crucially, this is not just about technical research, but also understanding social impacts.
African social scientists, legal experts, and philosophers should join technologists to research AI’s impact on African societies, ensuring that as we innovate, we also safeguard our values. When we develop AI with African realities in mind, we create technology that can better serve global humanity as well.
After all, solutions for intermittent internet connectivity or multilingual translation in Africa could benefit rural communities and diverse populations everywhere.
Africa’s pivotal role in AI is clear: we are a massive contributor of data and a growing market of tech-savvy people. The challenge now is to transform that role from passive to active — from being raw material for someone else’s algorithms to being co-authors of the AI age.
We have the opportunity to write our own digital future. That means staying vigilant about bias, insisting on our rights to our data, crafting and enforcing smart policies, and nurturing the talent that will build “Made in Africa” AI solutions.
The stakes could not be higher. AI is poised to influence every aspect of life — how we do business, how we learn, how we govern.
If Africa is merely an afterthought in this revolution, the inequalities of the past could deepen.
But if Africa takes ownership — as innovators, regulators, and equal partners — we can ensure AI becomes a force for inclusive growth and justice.
The journey has begun: entrepreneurs in Lagos and Addis Ababa are training AI in local languages; thinkers in Dakar and Nairobi are shaping ethical frameworks; and youths across the continent are learning to code AI algorithms, eager to make their mark.
The world should pay attention, because Africa’s involvement will shape the character of global AI.
Will AI be truly global, intelligent enough to understand and serve all humanity? Or will it remain narrow, only truly effective for those who developed it?
Africa’s stance can tip the balance. We stand at a crossroads where our continent can either be the testing ground for other people’s AI or the crucible of new AI paradigms. The latter is a future worth fighting for.
- Mutambasere is a development economist at the Africa Centre for Economic Justice, a thought leadership platform advocating for equitable technological and economic solutions across the continent.
