The AI Gender Gap: Why Women's Caution Makes Them the Leaders AI Needs

The AI gender gap shows up in almost every country and industry researchers have studied. Women are using generative AI less than men, and the usual explanation is that they need more confidence, more training and more time with the tools.

The newest research points somewhere more interesting. Many women are holding back because they're asking hard questions about privacy, accuracy and harm. Those are exactly the questions AI needs someone in the room to ask.

The AI gender gap is global

The gap is close to universal. A Harvard Business School working paper pulled together 18 studies covering more than 140,000 people and found it holds across nearly all regions, sectors and occupations.

Reporting on that paper puts women at about 20% less likely than men to use generative AI, at work and in everyday life.

Australia is no exception. Deloitte's 2025 predictions put workplace use of generative AI at 50% of Australian women, compared with 70% of men.

The gap also held when researchers gave women the same access to try the tools. Access alone doesn't explain it.

Why women are holding back from AI

Most explanations so far have focused on access, digital skills and confidence. A 2026 study from the Oxford Internet Institute argues that picture is incomplete.

The researchers looked at more than 9,000 UK adults. Men were more likely to use generative AI weekly for personal tasks (20.9% compared with 15.5% of women). The gap widened among people worried about AI's effects on mental health, the environment, privacy and jobs.

Two findings stood out to me. Among younger adults, better AI skills went with a much bigger jump in use for men than for women. What moved women's use was optimism about AI's impact on society, which went with a rise from 14% to 34%.

In plain terms, many women want to know this technology is safe, fair and worth trusting before they hand it their work. Deloitte sees the same pattern: women express less trust than men that AI providers will keep their data secure.

Women's questions about AI are governance questions

Who gets this data? What happens if the answer is wrong? Who's accountable when it goes sideways? Those questions often get labelled as hesitation. In governance and risk work, asking them is the job.

The Oxford researchers make the same point. If hesitation reflects real, unresolved risks, closing the gap takes more than training. It takes safeguards, transparency, accountability and privacy protection, and they describe unequal adoption as partly a governance problem.

That lands close to home for me. My career is operations, HR, governance and risk - deciding who does what, writing the job description, setting the guardrails and knowing where the risk sits. A good AI setup needs exactly that. AI just adds a new name to the roster.

Staying out has a cost, though. The Harvard researchers warn of a self-reinforcing cycle: if women use AI less, the systems learn from data that under-represents women's needs, and the gap widens. The women asking the careful questions are the people who should be shaping how AI gets used.

How to use AI on your own terms this week

You don't have to choose between jumping in blind and sitting it out. Start with one small, low-risk job and run it the way you'd run any new hire.

1. Pick one task you do every week. A first draft of a client email, a meeting summary, a social caption. Something low stakes you can check in two minutes.
2. Write the guardrails before you start. Decide what never goes in, such as client names, health details or financial information, and write it down.
3. Check the work like a new staff member's. Read every output before it goes anywhere. You're still the one who signs off.
4. Read the tool's data policy. Check what it says it does with your conversations and which settings you can change.
5. Keep your judgement in charge. The tool drafts. You decide.

Closing the AI gender gap starts with the careful ones

Being careful about AI is a strength. It's the instinct that keeps people, data and decisions safe, and it matters most while the technology and the rules around it are still taking shape.

I've been testing AI for almost four years and have helped more than 500 founders use it in their businesses. The approach I trust keeps humanness and judgement at the centre, and lets AI give you time back for the work you love.

If that's how you want to use AI, come and see how I do it at Sqylark.

Sources

• Global Evidence on Gender Gaps and Generative AI - Otis, Delecourt, Cranney and Koning, Harvard Business School Working Paper 25-023, October 2024
• Women Worry, Men Adopt? Gendered Risk Perceptions and Generative AI Adoption - Stephany and Duszynski, Oxford Internet Institute, 2026
• Women and generative AI: the adoption gap is closing fast, but a trust gap persists - Deloitte TMT Predictions 2025
• Deloitte's 2025 TMT report finds gender gap in AI usage in the workplace - Australian Marketing Institute, April 2025
• Women 20% less likely to use generative AI than men, study finds - eWeek, September 2025