AIBRIEF
In occupations where AI can do more of the work, men's employment grew 6.3% for each step up Pew's AI exposure scale (how much AI can do a job's core tasks) while women's grew 0.
Pew Research Center published a fresh read of U.S. employment data this week, comparing job growth before and after generative AI went mainstream. The gains are not landing equally. For every one-point step up Pew's AI-exposure scale (a measure of how much AI can do or help with a job's core tasks, low in construction labor, higher in accounting), men's employment grew 6.3% per point of exposure. Women's grew 0.2%, effectively flat.
At the top of the scale, the gap widens. In the least AI-exposed occupations, women's employment actually grew faster than men's. In the most exposed, the pattern flips sharply: men added jobs, women barely moved.
The comparison window is 2017-19 versus 2023-26, using government employment data; Pew excludes 2020-22 because the COVID-19 pandemic reshaped employment for reasons unrelated to AI. The design is within-occupation, comparing men and women in the same job rather than "men's jobs" against "women's jobs." Pew is not suggesting that some occupations are inherently "men's work" or "women's work." The center also flags that the relationship between AI exposure and job growth is not necessarily direct: other changes during the period may have also affected employment.
Read as a signal, the gap turns into a design question. Where training access, hiring practice, and deployment choices land over the next two years will decide whether AI capability distributes broadly or concentrates further.