Gender Bias: AI Will Take More Jobs From Women Than From Men

New AI tools are poised to shake up vast swaths of the US workforce in the coming decades, and they’ll have a disproportionate effect on women, according to a study(Opens in a new window) by the Kenan Institute.

“Eight out of 10 women in the US workforce are in occupations highly exposed to generative AI automation vs. six out of 10 men,” the study finds. It defines “highly exposed” as positions where 25% to 50% of its tasks could be automated by generative AI.

The findings build off a Goldman Sachs report(Opens in a new window) that identified the top 15 occupations most likely to be automated by generative AI. The Kenan Institute then used data from the US Occupational Employment and Wage Statistics(Opens in a new window) report to find the gender breakdown in these occupations, shown in the table below.

(Credit: The Frank Hawkins Kenan Institute of Private Enterprise)

While there are fewer women in the workforce overall (74 million compared with 84 million men), women hold more roles that are on the automation chopping block (58.87 million compared with 48.62 million roles held by men). That means “almost 80% of women in the workforce are in occupations exposed to automation via generative AI vs. 58% of men,” the study finds.

About 70% of women work in white-collar roles, with the remaining 30% in blue-collar positions. For men, that ratio is about 50:50. So women are proportionally more exposed to AI automation.

“These are primarily knowledge-worker positions,” the study says. “Generative AI will have much less impact on jobs that require physical labor as, at this point in time, it lacks the ability to perform that type of work.” (Until Elon Musk’s Teslabot hits the factory floor, that is.)

The study also notes that automating jobs has historically been counterbalanced by the formation of new jobs. To keep up with the changes, the Kenan Institute recommends knowledge workers “become familiar [with] generative AI tools” and “remain well informed about AI trends…so they can find additional means of improving their value to their organizations.”

Another caveat regarding the findings: They don’t take into consideration a breakdown of position types within the broad occupation categories. “For example, in the legal profession, 52.6% of employees are women,” the study says. “However, the paralegal subcategory, which will be more likely to be impacted than other legal subcategories, is composed of 83.2% women.”

The Kenan Institute calls for further research on the subcategory level to get a true understanding of the impact of AI automation on gender and profession.