Microsoft Executive Describes AI-Era Careers as a Climbing Wall

Employment growth in occupations with higher generative AI exposure scores varied sharply by gender, while Microsoft Chief Economic Opportunity Officer Aneesh Raman described career advancement in the AI era as less linear.

At the Oct. 22 WIN Summit, Raman compared career paths to a climbing wall, with workers able to choose routes shaped by their skills, interests and opportunities. The metaphor described career advancement as having multiple paths instead of following a single upward ladder.

The analysis covered 480 occupations and assigned each an AI exposure score based on tasks generative AI could perform or assist with. Scores ranged from zero to 3.5. The measure estimated potential task exposure within an occupation; it did not track promotions or individual workers’ career paths.

For each one-point increase in an occupation’s score, employment growth was 6.3% for men and 0.2% for women. These figures describe changes in employment counts by occupation, rather than changes in the share of workers who were men or women.

Among workers with a high school diploma or less, employment growth per score point was 8.8% for men and -9.5% for women. The analysis compared employment in 2017-19 with January 2023 through June 2026, excluding 2020-22. It did not establish that AI caused the gender differences.

A separate 2022 academic comparison covered 4,871 associate professors at four-year colleges. Women reported less clarity than men about promotion criteria at each career stage. Less clarity at middle career stages was also associated with being both a woman and BIPOC. Those findings concern academic careers and do not establish how employers outside academia set promotion rules.

The workforce questions connect with TokenPost’s earlier coverage of public concern about AI’s career effects. The employment figures track job growth across occupations, while the academic findings address clarity about promotion criteria.