Women are falling behind in AI: Here's why it matters

We have a problem. And if we don't address it now, it will set women's careers back by a generation.

The numbers are stark and should alarm every leader, policymaker, and basically anyone who cares about an equitable future. Studies show that women are 16% less likely than men to use generative AI tools for work and only 28% of women report using AI regularly, compared to 45% 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% of men use generative AI weekly compared to just 59% of women.

So, why are women adopting AI slower than men, and why does it matter?

The explanation we often hear is that women are simply "less interested" in technology. The reality is far more complex and deeply rooted in how women experience risk, both personally and professionally.

Firstly, women face higher exposure to AI-related risks. Research published by the National Institutes of Health found that women are over-represented in administrative, clerical, and service roles that are most susceptible to AI disruption. The International Labour Organisation confirms this pattern, noting that in the Philippines, women face twice the rate of AI exposure as men, particularly young and educated women concentrated in roles that AI can automate or fundamentally transform. This isn't abstract fear. It's a rational response to a genuine threat. For many women, 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 target women. 

Secondly, there is a structural mismatch between how AI tools are designed and the specific challenges women face in career advancement. As Valerie Chapman, CEO of Ruth AI, recently wrote, the AI tools flooding the market were built by male-dominated teams for general purpose use. They do not address the distinct hurdles women navigate: negotiating salaries (a landmark study found only 7% of female MBA graduates negotiated their first salary, compared to 57% of men), building professional visibility, and overcoming workplace dynamics that consistently disadvantage women.

The cost of inaction

The gender wage gap already costs Australian women $51.8 billion annually. 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.

The compounding effect is severe as men's research productivity increased 6.4% more than that of women researchers following ChatGPT's release, widening an existing academic achievement gap. Whether AI ultimately delivers net benefits or harms, those who engage with these technologies accumulate different skills, networks, and opportunities than those who abstain. This creates new axes of occupational segregation that operate independently of the technology's ultimate success.

Globally, the picture is concerning to say the least. Women represent less than 26% of AI professionals worldwide, and in STEM fields, they account for less than one third of the workforce. This imbalance means the very systems shaping our future are being built without diverse perspectives. 

Why diversity in AI adoption matters for everyone

This is not just a women's issue. To put it simply, a workforce where half the population lags in AI literacy is a less productive and less innovative workforce.

Why? Because 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. We know that women in leadership positions 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 and at most it's your hardest competitive advantage. 

Practical steps for leaders to close the gap

The question is not whether women can use AI. They can and they will. The question is whether leaders will create the conditions for them to do so confidently and effectively.

1. Address the fear, don't dismiss it. Women's caution is grounded in genuine risk exposure. Leaders must acknowledge this openly and create psychological safety around experimentation. This means normalising "safe to fail" learning environments where employees can explore AI tools without fear of judgment or competence scrutiny.
2. Invest in targeted training, not generic workshops. Generic "intro to ChatGPT" sessions won't cut it. Training must address the specific use cases that matter for women's career advancement: salary negotiation, personal branding, content creation, and strategic visibility. Organisations should aim to demystify GenAI career pathways, encourage participation, and bridge the gap through mentorship initiatives.
3. Build confidence through structured practice. Research shows that women's lower adoption is partly explained by general risk aversion, therefore the antidote is repeated, low-stakes exposure. Create dedicated time for teams to experiment together, share wins and failures, and build collective AI literacy.
4. Ensure diverse voices in AI governance. Only 22% of AI professionals are women globally. This imbalance means decisions about which AI tools to adopt, how to implement them, and what ethical guardrails to apply are being made without adequate female perspective. Leaders must actively recruit women into AI leadership roles and ensure diverse representation on AI governance committees.
5. Implement flexible work models that support learning and experimentation. Women still bear a disproportionate share of caregiving responsibilities. Learning new AI skills requires time and mental bandwidth. Flexible schedules and dedicated learning time are not perks, they are strategic necessities.

The choice before us

It is estimated that 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 and 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 leaders choose to make it so.

The future of work is being built right now. The question is whether we build it with inclusion at its core, or we allow old inequalities to be hard wired into new technologies. The choice is ours. And we cannot afford to get it wrong.