Africa is poised for a Generative AI leap, as McKinsey has projected up to $100 billion annual value if barriers are cleared.
A report, QuantumBlack, AI by McKinsey, titled ‘Leading, not lagging: Africa’s gen AI opportunity’ has revealed that generative artificial intelligence (gen AI) could unlock $61 billion to $103 billion in additional annual economic value across several sectors.
“If broader forms of AI (including traditional machine learning and analytics) are included, the total value could be even more, exceeding $100 billion annually,” the report said.
McKinsey argued that this opportunity isn’t theoretical because Africa has already shown signs of being an early mover and is in a position to leapfrog many of the legacy constraints that have slowed development elsewhere.
But only if governments, businesses, and institutions move decisively to scale up adoption, invest in infrastructure, and build capacity, it noted.
The sector winners include banking, retail, consumer packaged goods (CPG), telecommunications, insurance, mining/heavy industry & energy, and the public sector (including health and education). These are the sectors where early adopters are already deploying gen AI in meaningful ways, McKinsey stated.
Analysing the use cases driving impact includes banking through hyper-personalised marketing, risk and credit operations, fraud detection, and legacy system modernisation.
Retailers are also using gen AI for virtual shopping assistants, marketing content generation, store operations, and optimising supply chains, the report stated.
Telcos are focusing on improved customer service (chatbots, agent assistants), network-management tools, and automating operations. In public sectors such as education and health, gen AI could help in learner assessment, personalised content, and streamlining workflows like clinical documentation or citizen service engagement.
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McKinsey’s report framed Africa’s position as a ‘leapfrog opportunity’, building on its experience with mobile payments, cloud adoption, and other digital infrastructure, the continent can skip some of the more painful technology evolutions that delayed other regions.
However, the report outlined barriers that threaten to limit this potential, which are “Infrastructure deficits; Many countries lack reliable power, high-performance computing, and regional cloud infrastructure. Outside of South Africa, cloud providers and compute infrastructure are often missing or costly.”
It also noted the skills gap where there is demand for AI and gen AI expertise, but fewer professionals are qualified in areas like prompt engineering, LLM deployment, domain-specific use cases, and so on.
There is also regulatory uncertainty as legal, privacy, and cross-border data issues are underdeveloped. In many places, policymakers are still defining frameworks, the report stated.
Good input data, knowledge repositories, and domain-specific datasets are lacking in many organisations. Poor data makes AI outputs less reliable, increases risks (including bias), and reduces trust, McKinsey noted.
It however, noted that some African organisations are already showing how to navigate these challenges. The report highlights a few shared traits of those leading in gen AI deployment, which include focus on one high-impact use case end-to-end before scaling across multiple pilots.
Combine gen AI with traditional AI and analytics, rather than seeing them as separate. Many high-value use cases rely on both and organise transformation by domains (such as customer operations, software engineering) so that gains in data infrastructure, workflows, and capabilities in one domain can feed others.
McKinsey said they gave embedded risk, legal, and compliance functions from the outset to avoid long delays, compliance pitfalls, or public trust issues.
