Old inequality, new speed: Why AI will hurt women and girls more than anyone else
A report says that by 2030, nearly eight in 10 women will be forced to move to another company or lose their job to AI and automation.
What you need to know:
- As AI reshapes work globally, Kenyan women risk being displaced first due to deep-rooted inequalities.
- Limited access to time, technology and opportunity continues to push girls behind in Kenya’s digital transition.
Somewhere in Kenya right now, a woman is doing her job well. She is answering calls, processing requests, managing the kind of work that keeps an organisation moving. She has built something from that job, stability, a routine, a way of contributing to her household.
She does not know that the technology designed to replace her is already running in other parts of the world, and that when it arrives here, nobody in the room where that decision is made will be thinking about her.
That is not a technology problem but an old inequality, now moving faster.
Every major economic shift has displaced women first, and the response has always been the same: a brief acknowledgement, a call to adapt, then attention shifts to whatever replaces the jobs that disappeared. AI is not a new story. It is the same story, moving faster, and Kenya is not ready, especially not for the women and girls who will feel it earliest.
Old inequality
The inequality AI is accelerating did not begin with technology. It begins earlier, in homes where a girl’s evening looks nothing like her brother’s. He finishes school and has time to explore. She comes home to cooking, water, laundry, childcare. By the time she rests, the day is gone. This is why women arrive late to economic shifts, not because they lack ability, but because their time has never been their own.
The issue becomes clearer when you look at smartphone access. Across Kenya, and particularly in rural areas, it is far more likely that a man owns a smartphone than a woman. A device is not just a device, it is access to information, to markets, to learning, to the tools that now shape who participates in the modern economy and who is left out.
When a girl comes home to a mother with a basic phone or none at all, and homework requires a download, she falls behind, not because she is less capable, but because access determines who moves forward and who does not.
The data shows how serious this is. Globally, seven out of every ten jobs at high risk of automation are held by women. In Kenyan schools, one computer serves roughly three students, and AI is nowhere in the curriculum, a gap that falls hardest on girls, who are already navigating more barriers than their male classmates. Women also hold fewer than 30 per cent of ICT jobs in this country, which means the starting point is already difficult.
AI familiarity
Young men are pulling ahead of young women on AI familiarity for reasons that are well known: more time, better access to devices, stronger encouragement, and fewer messages telling them that technology is not really their space. A boy spending his afternoon on a smartphone is exploring.
A girl doing the same is often considered to be neglecting something. Those attitudes are not neutral. Over time, they become gaps in jobs, income and opportunity.
Our education system is not closing this gap. The Competency-Based Education (CBE) lists digital literacy as a foundation. But a curriculum without devices, connectivity and trained teachers isnot a plan, just intent without delivery.
Girls in under-resourced schools are being prepared for a future that has already moved on, and those with the most to gain from genuine digital education are consistently the least served by what is available.
Where do we go from here? Schools have to move beyond listing digital literacy in a curriculum and actually deliver it, with working equipment and teachers who are prepared.
Time and tech access
Families have a role too, asking honestly whether the girl in the house has the same access to time and technology as the boy, and whether the answer is one they are comfortable with.
Employers making AI decisions need to ask who is not in the room and why. The government also needs to get ahead of this, because waiting until the jobs are gone before asking what happened to the women who held them is a pattern Kenya can no longer afford.
AI is already here, reshaping work and widening gaps that were never properly closed. The question is not whether women and girls will be affected; they already are, but whether the people with the power to respond will treat their futures as a genuine priority rather than a footnote in a policy document nobody reads.
A future built on the same inequalities as the past is not progress. It is just the past moving faster.
