But the authors of the report and news coverage of the report clearly overlooked something crucial: the coming disruption will not be gender-neutral. According to the U.S. Bureau of Labor Statistics (BLS), women are the majority in about 60% of the occupations listed.
AI is poised to leave everyone without bread, but women will likely have their bread taken from them first and fastest by this technology. In the 1980s, the advent of computers put many secretaries and data entry operators out of work (jobs mostly held by women), and today, the new wave of automation may disproportionately affect women workers. A new study by the International Labor Organization shows that in high-income countries, women are about three times as likely as men to have their jobs automated.
The computer revolution serves as a cautionary tale. Many of the women who lost their jobs to this revolution in the ’80s never recovered from the blow. They either moved on to worse paying jobs (usually in the service or caregiving industries) after a long period of unemployment, or dropped out of the labor force for good. The BLS followed the fate of workers who were then unemployed, and the findings are striking: women were more than twice as likely as men to leave the labor market.
Women are already economically worse off than men (they earn less, own less, and retire with less savings), so authorities need to prepare for the AI to hit women’s jobs harder and develop measures to soften the blow.
In developing these measures, they should remember that in the 1980s, not all secretaries, data entry operators and typists suffered equally: women who were able to adapt to the new technology and acquire new skills fared better.
Let’s put aside – for now – the question of the loss of meaning of the concept of “upskilling” in an era when AI is expected to surpass human intelligence. Instead, let’s assume that there will be some sort of transition period where things will be better for workers with AI skills than those without. According to PwC’s published Global AI Workplace Barometer, workers with AI skills will receive a 56% wage premium in 2025, well above the 25% premium reported a year earlier.
In other words, if we’re not going to let female workers become the first collateral damage of AI, we need to make sure they fully master the new technology – or at least to the same degree as their male counterparts.
Right now, roughly equal numbers of women and men use ChatGPT for personal use, but in the workplace, there’s a striking gender divide. According to a recent survey of workers in the US, 36% of men use generative AI at work on a daily basis, but only 25% of women do. It is also reported that 47% of men, but only 39% of women, confidently use the technology at work.
This disparity is probably due to the fact that women are more concerned about the active use of AI than men. So it’s a healthy skepticism that we should all have. But there’s another reason: companies are more invested in improving the AI skills of male employees rather than women. In a global survey of 12,000 professionals conducted this year by Randstad, 41% of men said their employer provides them with access to AI, but only 35% of women did. In addition, 38% of men said they had been given the opportunity to learn AI skills, while the figure for women was 33%.
Being less likely to use new technology and being less likely to use it is a dangerous combination for female workers, especially when companies are increasingly demanding “AI skills” when deciding who to retain and promote.
If left unchecked, employers face legal risks. In the UK, employment policies that systematically disadvantage women (and reducing their chances of gaining AI skills fits that definition) can be recognized – under the Equality Act 2010 – as indirect sex discrimination. And this is so even in cases where the company did not intend to discriminate against anyone. Under this law (and similar laws in other countries), it is the result that matters, not the intention.
Norina Herz,
Professor Emeritus at the Policy Lab at University College London.
University College London (UCL Policy Lab), where she directs AI research.
© Project Syndicate, 2025.
www.project-syndicate.org
