Why aren’t women using GenAI as much as men?

A new report is highlighting yet another way that women are falling behind men when it comes to tech: they are 35% more likely to use generative AI tools (GenAI) to write their resumes, and 81% more likely to use the tech to complete recruitment tasks.

In addition, comfort level plays a significant role in adoption, with 23 percent more men (74%) than women (60%) stating they are comfortable using AI in job searches.

Resume builder Enhancv surveyed 600 U.S. users of their software, and analyzed 26,193 user-generated resumes for insights around how individuals are utilizing AI tech tools during job searches.

Why aren’t women using GenAI as much as men?

That difference in comfort level arises from cultural influences, says Carmina Ravanera, senior research associate at the Institute for Gender and the Economy at the University of Toronto’s Rotman School of Management.

“Men are more likely to be in jobs or sectors where AI is probably more immediately useful to them, sectors like IT or engineering, things like that,” Ravanera says. “This job segregation is partially what, or a great deal of what, contributes to the gender gap in pay and in labour, and that's caused not by a lack of skill or ability, but by obviously, gender norms and gender socialization.”

In its Global Gender Gap Report 2024, the World Economic Forum (WEF) points out that the “drop to the top” (the statistically significant decrease in women in progressively more senior roles) is particularly drastic in STEM occupations. This phenomenon gives women a “double disadvantage” during workplace transitions, the report states, “as they continue to occupy the lower-growth, lower-paying jobs that are likely to be negatively affected in the short term.”

^{Source: World Economic Forum}

“We know that women are finishing STEM degrees at rates that are equal to or higher than men in certain fields, especially in the sciences, but then when they get into those jobs, it [is] the work environment itself that ends up being non-inclusive, not accommodating to their lives and to their needs,” says Ravanera.

“We've seen research showing that women, more than men, tend to care much more about an environment that they know is free of hostility and free of harassment and is inclusive…that's I think a main reason why we see a lot of women deciding to pursue other sectors despite their experience, because they don't feel like it's a good place for them to work.”

Women don’t see themselves in STEM

Demand for STEM skills (including AI, GenAI and big data) are increasing generally, but there is a disparity in how women and men view their future skills requirements, the WEF report continues.

A 2023 PwC international cross-industry survey of 54,000 individuals revealed that 54% of women and 61% of men expect the skills required to do their jobs will change significantly in the next five years. Further, men appear to have a clearer idea of how those skills will change (68%) compared to women respondents (62%).

The answer to this problem of shifting perspectives is increased training, says Ravanera.

Organizations should be taking steps to train their current employees now, to prepare them for those opportunities, “considering how they can help their workforce upskill to be able to take on new challenges or tasks that they anticipate that AI would be helpful in… it's definitely something that companies should take advantage of,” she says.

Gender gap in AI persisting in Canada

Brett Hotas, executive director of Future Workforce Development Strategy at TECHNATION Canada, has seen this disparity in AI skills playing out in their own programming. For example, in a program offering wage subsidies to SMEs providing work-integrating learning (WIL) opportunities to students, there are significantly fewer women participants in AI.

“We've seen over the past couple years, a 70% increase in requests for AI placements. However… we're only seeing a 4% increase of female placements in AI,” says Hotas. “So, just in our own kind of micro-system, we can also see this trend, so it's really alarming to us.”

Hotas points out that in addition to women continuing to be under-represented in AI roles, other visible minorities, particularly Black and Indigenous individuals, are being left out of the “AI boom” as well.

“A number of other Black-led and Indigenous-led groups are trying, putting in a lot of effort at helping to create career pathways for those groups. But when we start seeing women lagging behind men at using generative AI, we know that it's going to be even more disproportionately affected for Black and Indigenous women,” he says.

“We can't be doing that in 2024.”

Employer responsibility for educating workers in GenAI

“Perhaps most distressing,” according to the WEF, is that the gender gap is widest among the youngest group of workers, with 59% of women and 71% of men ages 18-24 reporting weekly use of GenAI.

“We are trapped in a vicious labour market cycle that prevents women in leadership, which in turn damages our economy,” states the WEF, explaining that even typically women-dominated industries see a dip in women in leadership.

^{Source: World Economic Forum}

Hotas points to a lack in emphasis on lifelong learning and upskilling in Canada as a main culprit of this persistent drop in women in leadership, especially in STEM. This is an area where employers should step in to fill those gaps in skills through employer-led learning, he says.

“I think it's up to employers, in an AI boom, to make sure that staff are being provided with upskilling opportunities, that space is being held for them, that companies are budgeting time and budgeting money to be able to provide education,” Hotas says.  

In response to employer sentiment that in-house education is expensive and takes employee attention away from their tasks, he points out the increasing popularity of micro credentials as an efficient way to upskill employees. Plus, aside from the economic and social benefits of providing education and training to employees, it is also a proven strategy for retention, he adds.

Shift in hiring away from skills matching to aptitude for learning

The traditional recruitment process is also standing in the way of women gaining access into the tech industry, Hotas says, stressing that a shift in the way recruiters find and select candidates is becoming more necessary as tech skills become more in demand.

“Quite often, recruiters have their deliverables, and they can be quite risk-averse, because obviously it's quite an investment bringing on a new employee,” he says. “But, at the same time, they're being less productive because they're potentially letting someone who had almost all the right skills pass them by.”

Technology and the skills required to work with it are changing at such a pace that expecting job candidates to be a perfect fit no longer works, Hotas says; instead, HR should be hiring for aptitude, and looking in unorthodox places for potential tech hires, such as business or research-heavy arts programs.

“The perfect candidate isn't going to be out there right now, especially during the sort of GenAI, AI boom, because things are changing so quickly, and because so many of us haven't been able to subscribe or be put into a system that lends itself to this concept of lifelong learning, continuous learning,” says Hotas.

“If you're a good recruiter, and you've done some thinking and some strategic thinking around it, and some planning… by budgeting for upskilling and providing micro credentialing, etc, to bridge some of the gaps that they're seeing in an otherwise completely, perfectly strong candidate.”