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AI will change women’s work; leadership must decide what’s next

July 29, 2026
in Human Resources
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AI will change women’s work; leadership must decide what’s next
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As leaders responsible for helping global organizations adopt AI, we spend our days discussing transformation strategies. Yet it wasn’t until we looked at workforce composition alongside automation exposure that the pattern became impossible to ignore. Women are more exposed to AI disruption and are less likely to experiment with the tools.

We strongly believe in the technology to help the world’s largest employers with talent acquisition and employee development, but in human resources, the stakes are higher because AI directly affects people.

The last time organizations were forced to rethink work at this scale, it was the internet. Before that came electricity and telephones. Each wave changed how companies functioned and how jobs were defined. AI is doing the same thing, only faster and with less time for workers to adjust.

AI has the potential to make work dramatically more productive, but productivity gains are only part of the equation. Leadership also has to decide who is trained and prepared for the future and who gets left behind.

See also: AI experimentation: Your next move to recruit Gen Z

Automation’s unseen trade-offs

The clearest example is secretaries and administrative assistants. In the United States, 2 million women hold these roles, which have an automation risk score of 96, meaning they are highly exposed.

Receptionists and information clerks account for 1.2 million jobs and also carry a 96 risk score, with more than 90% held by women. Bookkeeping, accounting and auditing clerks add another million-plus jobs with a 98 risk score and more than 84% held by women.

This isn’t about treating women differently, but about understanding where AI’s impact is likely to be concentrated so organizations can prepare people before disruption occurs. If 72% of clerical roles are held by women and AI is redesigning their jobs, then women are being asked to absorb the shock before the rest of the labor market feels it.

Why the room reacted

Co-author Christina Brown, VP & GM, Global Customer Value, Phenom

The data surprised us, even though we live and breathe AI daily. So we created a community for women in tech and talent and held our inaugural event in Chicago. HR executives from well-known retail, food, biotech and health care were there. It turns out we weren’t the only ones caught by surprise.

Some HR leaders knew something was off the minute they saw the numbers, while others hadn’t connected the dots at all.

AI’s adverse impact is compounded by the fact that women are lagging in AI adoption, which came as a surprise to many of the leaders.

Why the lag? Harvard research suggests women are more likely to worry that using AI is unethical or amounts to “cheating” at work, and those concerns are amplified when organizational rules are unclear. Other studies show women are less likely than men to trust AI providers to safeguard their data, which is associated with lower willingness to adopt AI tools.

Meaningful leadership actions that work

Maggie Allen, Phenom
Co-author Maggie Allen, VP & GM, Global Revenue Enablement & Solutions Consulting, Phenom

We don’t purport to have all the answers, but the first step in finding them is through conversation. Here are some ideas that could bridge the AI divide:

First, companies should run a real workforce assessment before they automate. Know which roles are exposed, who holds them and what happens next.

Second, build upskilling plans before layoffs, not after them. If a role is being redesigned, the transition path should already exist. And, allow for candid conversations that personalize the impact readiness for these roles.

Third, pay attention to the infrastructure requirements for automating diverse interview scheduling panels. This requires companies to first tag employees as diverse in their Human Capital Management system; the technology can’t make that organizational decision on its own.

Fourth, make sponsorship part of the operating model. Mentorship is useful, but sponsorship puts people in the room and makes their work visible. That’s especially important for women who are ready for more responsibility but aren’t always seen as the obvious choice.

Men have a real role to play in this effort. Advocate for women on high-stakes decisions and create the kind of culture where learning AI is visible and supported. Women bring essential capabilities to the workplace, notably empathy, compassion and a high degree of attention to detail. These attributes are of growing importance and are increasingly relied upon as organizations navigate the evolving future of work.

The signs of progress

We will know this is working when we see:

  • More women move from administrative and support roles into the places where workflow, policy and AI adoption are being designed.
  • Workforce transformation creating shared opportunities for adaptation and growth. As roles evolve, both men and women are positioned to benefit from new pathways, skills development and emerging career opportunities across the economy.
  • More women noy just using AI, but helping decide how it gets used.
  • Organizations stop asking whether AI is disruptive and start asking where it can be most effective, and whether they have fair career transition plans for affected employees.

AI is already changing work. The question is whether women will absorb a larger share of the impact, be intentionally positioned to lead through it or be reskilled for other roles. That choice belongs to leaders, and the decisions they make over the next few years will shape not only the future of women’s careers, but the strength of the workforce as a whole.


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