Two decades ago, an idea that seemed improbable was beginning to take shape in Kenya. Moving money between people and places using a mobile phone almost looks simplistic today. It had not been tried at scale elsewhere, and scepticism was understandable.
It took an in-person demonstration by Michael Joseph to persuade the then Finance minister John Michuki of M-Pesa’s potential.
Today, mobile money has transformed how millions of people transact, save trade. Its significance extends beyond payments. It demonstrated that Africa can develop technology-led solutions to local challenges and scale them into platforms with global relevance.
I was recently invited to participate in a fireside chat during McKinsey’s Tech, Media and Telco Regional Leaders Forum in Nairobi, where the conversation focused on how Africa now stands at the threshold of another transformation, powered by artificial intelligence (AI).
The chance is not simply to adopt technologies developed elsewhere, but to apply intelligence to existing digital infrastructure to unlock new economic and social value.
The continent has a young population, mobile-first consumers, established digital financial ecosystems and a culture of innovation shaped by necessity. These strengths provide a foundation for AI solutions grounded in local realities.
Globally, AI development increasingly recognises the value of context. Organisations with distinctive customer insights, behavioural data and deep market understanding can build more relevant solutions. Innovators such as Wonderful AI are adapting AI to local languages, including Sheng, demonstrating why systems must reflect how people actually communicate.
But local relevance alone will not deliver transformation. AI must be supported by reliable infrastructure, quality data and people equipped to use it.
Across industries, automation is changing how work gets done. Historically, technological advances have changed the nature of work rather than eliminated it altogether. AI will test that pattern, making continuous learning and workforce adaptation essential.
The lesson for African businesses is developing talent which must become as important as acquiring technology.
As AI becomes embedded in financial services, healthcare and public services, questions of privacy, accountability and security become more consequential. The same governance principles that underpin trusted financial systems must extend to AI, including clear accountability, auditing and ongoing model monitoring.
Regulation is often presented as an obstacle to innovation. In practice, clear and proportionate governance can create the confidence businesses and citizens need to embrace new technologies. Speed and safeguards need not be competing priorities; trust must be designed into systems from the outset.
Connectivity, affordable devices, digital literacy and relevant services determine who benefits from technological progress. Without deliberate inclusion, AI risks concentrating opportunity among those already connected and advantaged.
Partnerships between business, government and development institutions can extend its reach.
That potential extends to humanitarian assistance.
In partnership with GiveDirectly, Safaricom piloted AI-enabled poverty identification in Garsen, Tana River County. Using consented mobile metadata insights alongside household consumption data, the model supported the identification and verification of vulnerable households, with millions subsequently disbursed through M-Pesa to eligible, enrolled and consenting recipients.
The significance lies not in the algorithm alone, but in translating intelligence into targeted assistance.
Africa’s AI opportunity will ultimately be measured by what it enables people to do, the businesses it helps grow and the public services it improves.
M-Pesa showed that African innovation can move from a local challenge to a transformative platform. AI offers another such opportunity.