I hear a lot of women talk about how they’re nervous to use AI, or that they’re skeptical of it. And I understand why, but honestly it scares me. Because it means women are going to be left behind.
So I went to the source. I recently flew to Silicon Valley for the NVIDIA GTC conference. Not just because I’m interested in the tech, but because I wanted to understand what’s actually happening. I sat in rooms where I was one of very few women. I asked questions, and I listened. And I came back with a clearer picture of where this is all heading.
What I saw didn’t surprise me, but it did concern me. The rooms were overwhelmingly male. That meant that the conversations were technical, not human. The questions being asked tipped more in the direction of speed and scale, as opposed to safety or fairness. The presentations were about the technology itself, not what people would actually do with it.
This is what happens when only 26 per cent of AI professionals are women. The very systems shaping our future are being built without diverse perspectives.
But it’s worse than that. Let me explain.
Women are already 16 per cent less likely than men to use generative AI tools for work and only 28 per cent of women report using AI regularly, compared to 45 per cent of men.
The gap is widest among the youngest workers, the very people who will carry AI skills (or the lack of them) throughout four-decade careers. Among Gen Z, 71 per cent of men use generative AI weekly compared to just 59 per cent of women.
The explanation we often hear is that women are simply “less interested” in technology. The reality is far more complex and it runs across several fault lines at once.
For many of us, the first widespread encounter with generative AI wasn’t through productivity tools at work. It was through the explosion of non-consensual deepfakes, “nudify” apps, and AI-powered harassment campaigns that disproportionately targeted women.
I think about this every time I hear a tech leader say “people are afraid of AI.” Of course they are. For half the population, the first message they received about this technology was: we can use this to hurt you. Is it any surprise we were discouraged?
But that’s only part of the story.
Women are also more likely to fall into what I’d call the expert-first trap – the feeling that you need to fully understand something before you can claim it. Men are more likely to experiment first and look foolish second. When AI has a steep learning curve and the tools are changing weekly, that instinct toward mastery before action becomes a significant disadvantage.
There’s also a resource calculation that many women carry with them, because of the disproportionate cognitive and domestic load outside of work. Spending discretionary time on uncertain tech experimentation feels like a low-return bet when bandwidth is already stretched. What may appear to be fear or lack of ambition is actually a rational response to an irrational distribution of burden.
And then there’s the representation gap. The public faces of AI are overwhelmingly male, technical, and white. When women look for someone who resembles them to help them use these tools in ways relevant to their actual careers, they largely come up empty.
There’s also a structural mismatch between how AI tools are designed and the specific challenges women face in career advancement. The AI tools flooding the market were built by male dominated teams for general purpose use. They do not address the distinct hurdles we navigate, like negotiating salaries (studies show only seven per cent of female MBA graduates negotiated their first salary, compared to 57 per cent of men), building professional visibility, and overcoming workplace dynamics that consistently disadvantage women.
But here’s the thing. The gender pay gap already costs Australian women $51.8 billion annually. I believe that AI could help close this gap by providing tools for negotiation, visibility, and career acceleration. Instead, we are watching the technology meant to democratise capability become another mechanism of inequality.
This is not just a women’s issue. A workforce where half the population lags in AI literacy is a less productive, less innovative workforce.
When women are excluded from meaningful AI adoption, we lose their perspectives in shaping how the technology is applied. We lose solutions to problems that men may not even see. Women in leadership ask different questions, like “Will the user feel anxious?” rather than solely focusing on algorithmic precision. You can copy code, but you can’t copy connection. In the age of AI, trust isn’t a soft skill. At the very least it’s necessary. At most, it’s your hardest competitive advantage.
Here’s what I want women to understand: the skills that will matter most in the age of AI are skills we already have.
It’s critical thinking. It’s emotional intelligence. It’s the ability to connect, to listen, to lead with empathy. These aren’t “soft skills.” They’re the only skills that can’t be automated and are the primary differentiator in a world where technical capability is becoming foundational.
I’ve spent my career building these skills. And I’ve watched women around me do the same, often without recognition, often without the same opportunities men get to translate that capability into career acceleration.
The question we need to ask now is: how do we continue to build on our core skills, with confidence and with urgency?
The advice I’m about to give is a workaround, not a solution. The structural barriers – the bias, the design gaps, the under-representation – won’t fix themselves, and individual action doesn’t substitute for institutional accountability. But while we push for better, we also can’t afford to wait.
So the biggest piece of advice I can give you is this: Don’t let AI happen to you.
You don’t need formal education. You don’t need to go back to university. Start with YouTube or Instagram reels. Watch a few keynotes. There are brilliant people out there sharing everything they know, and they want you to learn.
I was at a conference recently where I watched a woman in the audience raise her hand and say, “I don’t know much about this yet, but I want to. Where should I start?” The speaker lit up. After the session, three people came up to her offering to help.
That’s all it takes. Curiosity. The willingness to say “I’m learning.”
If you’re employed, your company might put you on an “Intro to AI” course. That’s a start, but it’s insular. If you really want to understand what’s happening here, you have to spend some of your own time learning.
Put your hand up. Tell your manager you want to get involved. “I can be a subject matter expert. I can be an AI champion in my team.” If women don’t do that, these spaces will continue to be run by men.
Generative AI could add $4.4 trillion in annual value to the global economy. If women continue to lag in AI adoption, they will be excluded from a disproportionate share of that value creation. The careers of millions of women will be capped. Not because of lack of ability, but because of a failure of leadership to address the structural barriers that hold them back.
AI should be an equalising force in society. But it will not happen by accident. It will happen because we choose to make it so.