Not On My Watch: How We Stop AI from Replacing Women First
- Catherine Del Vecchio Fitz
- Jun 5, 2025
- 5 min read
Women’s jobs are nearly three times more likely to be displaced by AI. This is the moment to pay attention.
TL;DR:
A new UN report shows AI is nearly three times more likely to replace women’s jobs than men’s. The reason isn’t a lack of skill—it’s lack of access, time, and support. The roles most at risk are the ones women disproportionately hold, and unless we address this head-on, AI will only deepen the inequities that already exist.
I’ve embraced these tools fully. I love them. But I’ve also spent over a decade either pregnant, nursing, or raising small children while building my career. I know what it feels like to just keep your head above water—and I know I’ve had more support than many.
This report was a wake-up call. AI is already reshaping how work gets done. That part is inevitable. What isn’t inevitable is who gets left behind in the process.
The Stat That Stopped Me Cold
AI is nearly three times more likely to take a woman’s job than a man’s.
As Fortune put it, men are more likely to use generative AI at work—and as a result, more likely to benefit from the productivity gains that make them harder to replace.
In higher-income countries, the gap is even starker. Nearly 10% of women’s jobs are at high risk of automation, compared to just 3.5% of men’s.
This isn’t just about automating tasks. It’s about who gets to stay, who gets seen as adaptable, and who falls behind. And it’s not because women lack the skills. It’s because many haven’t had the same access, time, or support to explore these tools in the first place.
It doesn’t have to play out this way. And I’m not going to sit back and watch it happen.
It’s Not a Skills Gap. It’s an Access Gap.
Women can and do learn these tools quickly. In many cases, they use them more strategically—optimizing not just individual tasks, but entire workflows. The problem isn’t ability. The problem is opportunity.
Access to tools, time, training, and support still isn’t distributed equally. When you’re already stretched thin—balancing meetings, logistics, and caregiving—you’re not going to carve out extra time to “play around with AI,” especially if no one is showing you how or why it matters.
Some women worry they’ll be judged for using AI—seen as cutting corners or relying on shortcuts. And in environments where experimentation is informal or unspoken, that fear isn’t irrational.
I say this as someone who tends to lean in. I dove into these tools, and they’ve changed how I work, think, and build. But I’ve also spent more than a decade in some stage of caring for very small children, often while holding demanding roles. I know how it feels to operate at capacity. And I also know I’ve been fortunate—supported, flexible, and resourced in ways many women simply aren’t.
So I hadn’t fully grasped how uneven this adoption curve could be until I saw the numbers. And now that I have, I’m paying attention. Closely.
The Patterns We Risk Reinforcing
AI doesn't start with bias—but it learns from what we give it. And what we’ve given it, across industries, is a reflection of how work has been distributed and valued for decades.
When AI is trained on historical data, it picks up the same patterns we’ve been trying to fix: who gets hired, who gets promoted, who gets support, and who gets sidelined. It doesn’t question those patterns—it just scales them.
We’ve already seen it happen. Resume-screening tools that downgrade women’s experience. Performance review systems that reinforce existing disparities. Recommendation engines that push men toward leadership roles and women toward support work.
Unless we interrupt those defaults, AI will quietly carry them forward, at speed and at scale—and that means the very people who were under-recognized before will now be the first ones left behind.
That’s not just a technical problem. It’s a leadership one.
What Needs to Happen—Now
This isn’t about fear. It’s about responsibility. If we know the risks, we don’t get to sit this out. Here's where we start:
1. Make AI usable for the people who are actually doing the work.
Most AI training is still designed for tech teams or leadership—not the people in operations, admin, support, and coordination roles where automation is already creeping in. We need training that fits into the flow of real jobs, not theoretical demos. That means short, specific use cases, tailored to the actual tools people use every day. If your "training" assumes time, confidence, or extra capacity, it's already failing the people who need it most.
2. Focus on empowerment, not replacement.
Too much of the current conversation treats AI like a replacement plan—how fast can we automate, who can we downsize, what can we “streamline.” I’ve been vocal about the value of efficiency. I believe in using technology to make work faster, cleaner, and more sustainable. But that’s not the same thing as cutting people out of the equation.
Efficiency should make teams stronger and able to do more with what they have—not smaller.
The real opportunity is using AI to move people up the value chain, not out of it. That starts with showing employees how to reduce low-value work so they can focus on what only humans do best—strategy, insight, judgment, connection.
3. Shift from hype to fluency.
The hype cycle isn’t helping anyone. What people need isn’t more headlines—it’s hands-on fluency. That doesn’t mean learning to code. It means understanding where these tools fit, how to test them safely, and how to apply them to real problems. When fluency is treated like a luxury, people opt out. When it’s treated as a strategic skill, they lean in.
And let’s be honest: this doesn’t just fall on individuals. It’s on managers, teams, and leaders to create the space, the culture, and the expectations for AI adoption that actually works. If we want AI to benefit everyone, it’s leadership’s job to make sure everyone is invited in.
From Vulnerable to Unstoppable
The UN report is a wake-up call—and an important one. But it’s not a prediction of what has to happen. It’s a chance to do something different.
AI is moving fast, and it’s not going to slow down. The question is how we move forward without leaving behind the people who’ve already carried more than their share. That includes the women whose work has too often been undervalued, overlooked, or invisible—and who now risk being automated out of the picture entirely.
The future of work can absolutely be better. It can be smarter, fairer, and more human—but only if we build it that way. That starts now, with the systems, training, and choices we make today.
We’ve seen these patterns before. But if we let them take root in AI, they’ll spread faster and further than ever—and that’s exactly what I’m here to push back against.
Thanks for reading,
—Savvyn (your partner in ruthless efficiency)
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