Do women use less AI than men?
Mar 22, 2026
A few weeks ago, I was at an International Women’s Day event, listening to a keynote of the leader of a large women’s professional network.
She said something that stuck with me.
“Women are using AI far less than men. And the problem with that is - the less women interact with these tools, the less women’s voices and perspectives shape how AI learns. The gender gap we already have could get baked into the technology permanently.”
I went home and started digging. Is this actually true? How big is the gap? And why is it happening?
What I found changed how I think about AI.
The AI gender gap is real
Harvard Business School researchers pulled together 18 global studies on AI adoption. The finding: women are 20-25% less likely to use generative AI than men.
This wasn’t one small survey. The research included a University of Chicago study of 100,000 workers, a World Bank analysis of global internet traffic, and the McKinsey/LeanIn Women in the Workplace report, which covers 124 organisations and 3 million employees. (The studies are linked at the bottom of this email)
The gap is consistent across industries and countries.
Why women hold back
Three reasons came up across the research. One of them I found particularly hard to read, because I recognised myself in it.
The first reason: women are more worried than men about looking lazy or like they’re cheating.
Here’s the psychology behind it. Research on the authority gap shows that in most workplaces, women start from a lower baseline of assumed competence. Both men and women tend to assume, often without realising it, that women are less capable. Women in technical fields feel this particularly strongly.
One response to that? We protect our competence by showing our work. If the process is visible and rigorous, our capability is harder to question. So we do things manually and don’t take shortcuts.
The problem is that AI looks like a shortcut - even when it isn’t.
Here’s the reframe: using AI to produce better analysis, clearer communication, or faster research is not evidence that you can’t think. It’s evidence that you can. A surgeon who uses the best tools available is not less skilled than one who refuses to. She’s more effective.
The second reason: your manager is probably not encouraging you to try AI. According to the Women in the Workplace report, only 21% of women are encouraged by their manager to use AI at work, compared to 33% of men. In some roles, managers assume automation is coming anyway, so why invest in the person?
That means the permission you’re waiting for may not arrive. You may need to give it to yourself.
The third reason is smaller but worth naming: women report more concern about the risks of AI - data privacy, mental health effects, environmental cost. These are legitimate concerns. The practical answer is to learn enough about the tools to use them carefully, rather than avoiding them altogether.
Why this matters for your career
The Norwegian School of Economics surveyed 1,100 managers. 65% said they would promote a worker who used AI to increase their output.
PwC’s Global AI Jobs Barometer found that roles requiring AI skills pay around 50% more than equivalent roles without that exposure.
This is not a distant trend. It is happening now, in the organisations where you work.
So what can you do about it?
Two actions for you
First: Make it a habit to “zoom out” of your work from time to time, and question how you do things. Is there something you could use AI for to speed it up or make it better?
The more you think about this, the more you will spot opportunities. You don’t need to become knowledgeable in all the AI developments, but you do need to question the way you work, so that you naturally pick up some AI tools. Here is a newsletter I can highly recommend about how to think about AI: Futureproof with AI.
Second, and this goes hand in hand with picking up more AI tools: protect your thinking. Studies are starting to show that when we outsource our thinking to AI constantly, our critical thinking gets weaker. Your brain stops doing the deep work it used to do, because it doesn’t need to. So you need to be very careful about when to use AI and when not.
I noticed this in myself. I started reaching for Claude before I’d even tried to think through a problem. So I introduced AI-free mornings on some days of the week. For the first two or three hours of my working day, I don’t use any AI tools. I write, think, and analyse the way I used to. I find it keeps my thinking sharp - and when I then bring in the AI tools, it really accelerates me, as I am conscious about what I want to achieve with it.
The goal isn’t to become an AI expert. It’s to make sure this is a tool that works for you - not a gap that works against you.
PS: Here are the links to the research I mentioned, if you want to dive deeper:
Harvard Business School working paper: Global Evidence on Gender Gaps and Generative AI
University of Chicago working paper: The Adoption of ChatGPT
World Bank Group policy research working paper: Who on Earth Is Using Generative AI?