Africa’s ambition to build a thriving artificial intelligence (AI) economy, potentially contributing up to $1 trillion to GDP by 2035, is unfolding against a backdrop of significant infrastructure constraints. Unlike the well-resourced AI ecosystems of the Global North, African countries must find ways to develop and deploy AI that reflect the continent’s realities. This means embracing lightweight, localised and energy-efficient solutions while placing trust, governance and local relevance at the centre of the AI conversation.
Africa currently accounts for less than 1% of global data centre capacity despite being home to about 17% of the world’s population. South Africa accounts for a large share of the continent’s capacity, while countries such as Nigeria continue to operate with relatively limited infrastructure for their populations. High electricity costs, unreliable grids and dependence on backup generators further increase the cost of running data-intensive AI systems. These constraints make it difficult for Africa to simply replicate the infrastructure-heavy AI models developed elsewhere.
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The connectivity gap adds another layer to the challenge. Internet access remains significantly lower in Africa than in many other regions, particularly in rural communities. For AI applications that require real-time data processing, routing information through distant overseas data centres can also create latency problems. However, the expansion of 5G and other broadband technologies could enable more distributed AI systems, allowing data to be processed closer to users rather than relying entirely on centralised infrastructure.
This is where edge AI presents an important opportunity. By processing data locally on smartphones, computers and other connected devices, edge AI can reduce dependence on large cloud data centres and lower bandwidth requirements. Its potential applications are particularly relevant to African economies, where intermittent connectivity and limited computing infrastructure remain common. From agricultural diagnostics to financial services and energy management, AI systems designed to function with limited connectivity could deliver practical benefits to millions of people.
Africa’s energy challenge could also become an opportunity for a different model of AI development. The continent possesses enormous solar potential but continues to use only a fraction of it. Expanding renewable energy alongside decentralised digital infrastructure could provide cleaner and more reliable power for AI applications. Initiatives such as the African Development Bank’s Desert to Power programme demonstrate the potential of combining renewable energy investment with broader digital and economic development.
The strongest opportunities are likely to emerge from applications that solve specific local problems. AI-powered agricultural tools can help farmers identify crop diseases, optimise inputs and improve yields. Financial technology companies are using alternative data to expand access to credit, while healthcare providers are exploring AI-assisted diagnostics in areas where specialist medical expertise is limited. These applications demonstrate that Africa does not necessarily need the most computationally intensive AI systems; it needs systems that are affordable, accessible and capable of addressing real economic and social challenges.
Language is another critical frontier. Africa is home to thousands of languages, yet only a small number are adequately represented in mainstream AI systems. This creates a major barrier to inclusion. An AI tool that works effectively in English or French may remain inaccessible to millions of Africans who communicate primarily in Hausa, Yoruba, Amharic, Swahili or other local languages. African researchers and technology communities are beginning to address this gap through open-source language projects and locally developed datasets. Building stronger African-language AI models could improve access while ensuring that the continent’s cultural and linguistic diversity is reflected in emerging technologies.
The economic stakes are considerable. Increased investment in digital infrastructure and AI could raise productivity across sectors, create new businesses and expand access to services. But without stronger indigenous capabilities, Africa risks becoming primarily a consumer of AI technologies developed elsewhere. That could deepen existing technological and economic dependencies, particularly if African data is processed abroad and local businesses remain dependent on foreign platforms.
Trust will determine how widely these technologies are adopted. Concerns about data privacy, surveillance, algorithmic bias and the misuse of personal information can undermine public confidence in AI. For African countries, building trust requires clear rules around data protection, transparency and accountability. The African Union’s Continental AI Strategy provides an important framework, but national governments will also need to translate broad principles into effective regulation and enforcement.
Nigeria illustrates both the opportunity and the challenge. As Africa’s largest economy and one of its leading technology markets, the country has attracted significant investment in its startup ecosystem and is developing policies aimed at strengthening AI skills and infrastructure. Yet persistent electricity and connectivity challenges continue to constrain the scale at which advanced technologies can operate. Nigeria’s experience will be closely watched as it seeks to balance rapid technological adoption with the development of local capabilities.
Africa’s AI future will not necessarily be built by copying Silicon Valley. The continent has an opportunity to develop a different model — one that combines edge computing, renewable energy, locally relevant applications, African-language models and responsible governance.
The objective should not simply be to consume AI, but to build the capacity to develop, govern and commercialise it. If African countries can invest in skills, infrastructure, data and institutions while creating an environment where innovation can flourish, AI could become a powerful driver of productivity and inclusion.
The question facing Africa is therefore no longer whether the continent will adopt artificial intelligence. It is whether it will have the capacity to shape the technology, rather than simply consume it.
