Artificial intelligence (AI) is rewriting the rules of global competitiveness—and Africa stands at a crossroads. While the U.S., China, and Europe pour billions into AI infrastructure, talent, and applications, the continent’s innovators face systemic barriers that threaten to relegate Africa to the role of consumer rather than creator. In this Op-Ed, Mayowa Olugbile, CEO of Itana, examines the opportunities and challenges shaping Africa’s place in the AI revolution—and outlines what it will take to build a self-sustaining, globally relevant ecosystem.
Africa and the AI race: Building from the ground up
“Artificial intelligence (AI) is increasingly described as the defining technology of our era—a force capable of transforming industries, economies, and indeed whole societies. The United States, China, and Europe are pouring vast sums into AI research, infrastructure, and applications. Indeed, U.S. private AI investment alone hit $109.1 billion in 2024.
Given these trends and the eye-watering sums being committed to AI development around the world, Africa risks being left behind if it does not address the structural challenges that currently limit its participation.
Talent is ready, but access is limited
Africa is rich in talent and ambition. Across the continent, universities, research institutes, and innovation hubs are producing skilled engineers, data scientists, and entrepreneurs capable of engaging with cutting-edge AI. Many of the continent’s most urgent challenges—ensuring food security, expanding access to healthcare, and increasing financial inclusion—are precisely the kinds of problems AI could help solve.
Entrepreneurs are already taking notice. SAP Research notes that roughly 2,500 AI-focused companies are operating in Africa, developing solutions from predictive farming analytics to AI-driven financial tools for underserved populations. The World Economic Forum predicts that AI and emerging technologies could add as much as $1.5 trillion to Africa’s GDP by 2030, reflecting both the potential and the demand for locally relevant applications.
Yet despite this talent and ambition, African innovators face persistent barriers that prevent the creation and scaling of advanced AI systems. Without intervention, the continent risks becoming a consumer of externally developed AI, reliant on tools that may not reflect African languages, contexts, or priorities.
Infrastructure gaps: A major constraint
The most immediate obstacle is infrastructure. Training sophisticated AI models—like large language models—requires access to powerful computing resources, typically provided through high-performance GPUs. In most African countries, renting these systems overseas is prohibitively expensive, and local infrastructure often cannot support prolonged, energy-intensive AI training sessions.
Simply put, the continent lacks the widespread, affordable computing power needed for AI experimentation at scale. Without it, entrepreneurs cannot test ideas effectively, and local AI industries cannot grow beyond proof-of-concept stages.
Data and sovereignty challenges
Data is another critical limitation. Effective AI relies on large, high-quality datasets governed by frameworks that safeguard privacy, security, and ethical use. African governments are rightly cautious about how citizens’ data is stored and processed, often requiring it to remain within national borders.
However, local data storage and processing can be prohibitively expensive. Many institutions rely on foreign cloud providers, which raises complex questions around sovereignty and control. Dependence on external infrastructure limits Africa’s ability to influence how AI systems are trained and deployed in local contexts, potentially undermining both trust and relevance.
The brain drain factor
Africa has abundant digital talent, but retaining skilled AI practitioners remains a major challenge. Many of the continent’s brightest minds leave in search of better-resourced environments and opportunities to work on advanced projects. This “brain drain” weakens local ecosystems and perpetuates reliance on foreign expertise, making it difficult to develop a self-sustaining AI industry.
Without addressing infrastructure, data, and talent retention, Africa risks being a passive player in a field that will shape the global economy for decades. Even as AI becomes embedded in everyday tools—financial services, agricultural systems, or healthcare delivery—African innovators may have little influence over how these systems are built or applied locally.
The resulting risk is that Africa becomes unable to harness this potentially transformative technology to its full potential.
The costs of dependence
Relying heavily on foreign-built AI systems carries multiple risks. Cultural and linguistic gaps can emerge when tools are trained primarily on Western datasets, potentially leading to errors in healthcare, education, or governance applications.
Economically, dependence also limits opportunity. The global AI industry is set to generate trillions of dollars in value, but if African firms remain consumers rather than creators, the continent misses out on a major source of growth. Developing local AI value chains is essential to ensure Africa captures a meaningful share of the industry’s economic and strategic benefits.
Sovereignty is another concern. As AI becomes integral to national security, infrastructure management, and governance, over-reliance on foreign systems could expose vulnerabilities and compromise decision-making autonomy.
Encouraging developments
Despite these challenges, there are reasons for optimism. Universities and research centres are launching AI labs, and governments are developing strategies to support responsible AI innovation. Startups continue to demonstrate ingenuity, particularly in sectors such as agriculture, logistics, and healthcare.
While venture funding has slowed since 2021, the creativity and resilience of Africa’s AI entrepreneurs remain evident. Even global industry leaders are taking note. Sam Altman, CEO of OpenAI, has highlighted Africa as a rapidly growing and strategically important market in the coming decades. The question now is how to convert potential into measurable, sustainable outcomes.
Steps toward a sustainable AI ecosystem
Africa’s path to meaningful participation in the global AI economy rests on three priorities.
First, the continent must invest in accessible computing infrastructure—regional data centres, shared GPU hubs, and innovative financing mechanisms that make high-performance computing affordable for local entrepreneurs.
Second, compliant and cost-effective data frameworks are essential. Governments, regulators, and private-sector actors need to collaborate to ensure sensitive information can be stored and processed locally, enabling both innovation and sovereignty.
Third, retention of talent is critical. African engineers and innovators need ecosystems where they can develop, test, and scale AI solutions without leaving the continent. This includes access to mentorship, funding, collaborative networks, and professional development opportunities.
Africa’s unique role in AI
Africa’s approach to AI does not need to replicate the strategies of the US, China, or Europe. The continent’s strength lies in applying AI to immediate, high-impact challenges—optimizing smallholder farm yields, extending healthcare to underserved communities, and improving local infrastructure and logistics.
Moving from consumer to contributor requires confronting the structural barriers head-on. Infrastructure, data sovereignty, and talent retention are not optional—they are the bedrock for meaningful participation in the global AI economy.
Allowing Africa to fall behind in the AI race would be bad for the rest of the world, too. If Africa is left out, the world loses the perspectives, datasets, and innovations the continent uniquely offers. The challenge is clear: the next wave of technological transformation must be built with Africa, by Africans, and for the world.“
© MayowaOlugbile (2025)