Africa’s push to adopt artificial intelligence (AI) is gaining pace, but persistent infrastructure gaps, particularly in power and data centre capacity, threaten to slow progress across the continent.
This is according to Oluwafiropo Tobi Ogundare, territory sales lead for West Africa and Mauritius at Red Hat, speaking during the company’s media roundtable held in Johannesburg on Monday.
The insight comes as an analysis from McKinsey notes that African economies could unlock up to $100 billion in annual economic value across multiple sectors from generative AI alone, in addition to the still-untapped potential from traditional AI and machine learning.
Ogundare stated that while demand for AI is undeniable and growing, most nations across the region are not yet positioned to scale adoption effectively.
“If we look at the cost that comes with AI, you would realise that across East and West Africa and the Indian Ocean islands, there is no country well positioned right now to burst into that AI or scale into that AI world, because there are inherent problems: cost and infrastructure, which is the biggest of them all.”
Across the regions he oversees, Ogundare noted a consistent trend, saying organisations are eager to adopt emerging technologies, but foundational challenges remain, including modernising legacy systems, optimising infrastructure, and ensuring long-term support for critical platforms.
“The infrastructure runs the heart of everything. If customers want to run AI-enabled workloads or cloud applications, they need infrastructure that can support all of this,” said Ogundare.
As a result, enterprises are taking a cautious and incremental approach to AI adoption, rather than pursuing large-scale deployments.
“We do not want to take a big bang approach with AI,” emphasised the Red Hat executive. Instead, organisations are embedding AI capabilities gradually across systems, focusing on smaller, manageable use cases that align with existing capacity and budgets.
At the same time, a notable shift is visible in cloud strategies. While cloud adoption continues, some organisations are re-evaluating their approach.
“We are seeing customers repatriating data from the cloud because of security concerns and cost,” he noted, highlighting the growing importance of hybrid and flexible IT environments.
digital sovereignty is also becoming a key priority across African markets. Governments and enterprises are prioritising control over data, infrastructure, and AI models, driven by regulatory requirements and the need to build locally relevant solutions.
This has placed open-source technologies at the centre of many AI and digital transformation strategies, as organisations look to avoid vendor lock-in and maintain greater control over their technology stacks.
“Open source is at the core; everyone wants to avoid vendor lock-in,” he added.
Despite the challenges, he emphasised that Africa is not falling behind in the global AI race. Instead, the continent is competing at a different pace.
“Africa is not lagging behind; we are competing effectively,” he said, pointing to growing investment and collaboration across markets.
Examples include increasing activity in countries such as Nigeria and Mauritius, where governments, telecoms operators, and private sector players are collaborating to develop national AI strategies and supporting infrastructure.
However, the success of these initiatives will depend heavily on public sector leadership and investment.
According to Ogundare, governments play a critical role in enabling the infrastructure required to support AI at scale.
Power availability remains a pressing issue, as data centres and AI workloads require a significant and reliable energy supply. Without it, even well-funded projects risk delays or cancellation.
Ogundare stressed that addressing these gaps will require coordinated efforts between governments, telecoms providers, technology vendors, and other stakeholders.
“There is still a lot of work to be done in Africa. We are not there yet, but we are seeing the willingness to invest and close those gaps.”
As global and regional players continue to invest in Africa’s digital ecosystem, the continent’s AI trajectory will depend not only on innovation but on its ability to build and sustain the infrastructure needed to support it.
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