The global debate about Artificial Intelligence (AI) and its impact on jobs has been dominated by a simple but polarising narrative: AI will either cause mass unemployment or usher in a productivity boom benefiting everyone. However, while much of this discussion has focused on high-income economies, the reality of African workers is vastly different. What does AI really mean for African workers – many of whom are farmers, drivers, or traders rather than software engineers or graphic designers?
Mapping AI exposure in Kenya
This Kenyan case study offers one of the first data-driven insights into this question. Using microdata from the 2022 Kenya Continuous Household Survey, each reported occupation was classified into one of six AI exposure gradients, following the International Labour Organization’s (ILO) Generative AI and Jobs framework. This analysis provides a clear snapshot of who is most vulnerable to AI disruption, their incomes and where they live.
For the first time, to our knowledge, we can see how Kenya’s labour force is distributed across occupations that are highly automatable, moderately at risk or largely untouched. And the picture is striking.
Kenya was chosen for this prototype precisely because of its high-quality, publicly available labour market data, making it an ideal testing ground for a methodology that could be applied across Africa.
While this is only the beginning – a prototype approach built on publicly available data and expert mappings – it’s a critical starting point. To truly prepare African economies for the coming wave of automation, a formalised research effort is critical – one that would bring together international donors, governments, employers, trade unions and AI companies to build a shared evidence base. This will help countries not just to measure their exposure, but to design targeted interventions, track progress and make sure that AI adoption leads to better jobs, not fewer jobs. The window for action is closing fast.
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