Kira WebAfrica | June 10 2025
A new study presented at the Global AI Summit in Kigali has cast a stark light on how artificial intelligence could redraw Africa’s outsourcing sector The research shows that women hold a disproportionate share of tasks most at risk of automation and could face steeper job losses by the end of the decade
Africa’s outsourcing industry employs thousands in data entry content moderation customer support and transcription Many of these roles are entry level and lower paid making them prime targets for generative AI and large language models that can handle repetitive digital work far faster and at lower cost.
Key findings from the report underline the scale of the challenge
✔Women’s roles are projected to be ten percent more likely to be automated than men’s by 2030
✔Entry level tasks account for sixty eight percent of the current workforce across major outsourcing hubs such as Nairobi Lagos and Cape Town
✔Up to forty percent of existing job tasks could be replaced or radically reshaped as AI tools become cheaper and more accurate
Researchers argue that gender imbalances in job type and career mobility leave women exposed to automation shocks Many female workers enter outsourcing via content tagging or basic customer queries while men are likelier to be in technical support or supervisory roles which face slower automation
The study calls for a comprehensive upskilling plan aimed at women and young workers First it urges outsourcing firms to integrate AI literacy into onboarding so employees can shift from manual tagging to supervising machine outputs Second it recommends public‑private scholarship funds for women to train in data analytics prompt engineering and AI quality assurance Finally it suggests revising procurement rules so contracts reward vendors that can show gender balanced career progression.
Several African governments are already reacting Rwanda is expanding its digital skilling curriculum to include AI ethics and model validation Kenya’s ICT ministry has signaled new targets for female participation in advanced tech training.
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