Artificial intelligence is no longer a distant concept in Kenya. It is quietly approving loans, answering customer queries, editing text, optimising transport routes and flagging medical risks—often faster and cheaper than humans ever could.
But as the technology accelerates, a pressing question is emerging: can Kenyan society keep pace?
At the World Economic Forum in Davos, JP Morgan Chase CEO Jamie Dimon issued a stark warning that AI, if rolled out too aggressively, could destabilise societies by displacing workers faster than economies can absorb them. His message, though delivered in a global forum, echoes loudly in Kenya, where livelihoods for millions depend on jobs already feeling the pressure of automation.
A Silent Shift in Kenyan Workplaces.
Across Nairobi and other urban centres, AI systems are steadily taking on tasks once handled by people. Banks increasingly rely on automated credit scoring and chatbots. Telecommunications firms use AI to resolve customer complaints. Newsrooms, marketing agencies and content studios are experimenting with AI tools that can write, edit and translate in seconds.
In logistics and transport, algorithm-driven systems are reshaping delivery networks, reducing reliance on drivers while increasing efficiency. Though fully autonomous vehicles may still be years away, the direction of travel is clear.
For a country with a youthful population and limited formal employment opportunities, the implications are profound.
“Kenya cannot afford sudden job shocks,” says a labour economist in Nairobi. “When technology moves faster than job creation, frustration builds—and frustration has consequences.”
Informal Workers at Greatest Risk.
Unlike advanced economies, Kenya’s workforce is dominated by the informal sector. Boda boda riders, matatu crews, delivery drivers, casual clerks and small traders form the backbone of urban employment. Many of these roles are vulnerable to AI-driven efficiencies.
Dimon used the example of millions of American truck drivers who could be displaced by driverless vehicles. In Kenya, a similar disruption could affect public transport operators and delivery workers if automation is introduced without a transition plan.
Moving someone from a stable income to precarious work overnight, experts warn, is a recipe for social strain.
Growth That Leaves No One Behind?
Kenya’s digital ambitions are bold. Government strategies promote AI as a driver of productivity, innovation and global competitiveness. In healthcare, AI offers promise in diagnostics and disease monitoring. In agriculture, smart systems can boost yields and reduce losses. In public administration, automation could reduce inefficiency and corruption.
Yet these gains come with trade-offs.
Without deliberate policies, AI risks concentrating opportunity among those with digital skills while marginalising workers who lack access to training and education. The result could be deeper inequality—between urban and rural areas, skilled and unskilled workers, and young people with access to technology and those without.
Why Timing Matters.
Dimon’s central argument was not to stop AI, but to slow its impact on people.
For Kenya, this means phasing adoption in a way that allows workers to adapt. Technical training institutes, universities and private companies could play a key role in reskilling workers into new roles such as system maintenance, data handling, digital logistics and AI oversight.
Social safety nets—often overlooked in technology debates—may also need strengthening. Temporary income support, retraining subsidies and job placement programmes could help prevent displacement from turning into despair.
A Policy Window That Won’t Stay Open Forever.
Kenya still has time to prepare. AI adoption is accelerating, but it is not yet irreversible. What is missing, analysts say, is a coordinated national response that links technology policy with labour planning.
This includes gathering data on which sectors face the highest risk, engaging workers and unions early, and ensuring that productivity gains translate into shared benefits rather than social tension.
The lesson from Davos is clear: technological progress without social preparation comes at a cost.
As AI reshapes the future of work, Kenya’s challenge will not be whether to adopt it—but whether it can do so without leaving millions behind.
