Immigration and Regional Specialization in AI

Abstract

I examine the specialization of US commuting zones in AI-related occupations over the 2000 to
2018 period. I define AI-related jobs based on keywords in Census occupational titles. Using the
approach in Lin (2011) to identify new work, I measure job growth related to AI by weighting
employment growth in AI-related occupations by the share of job titles in these occupations that
were added after 1990. Overall, regional specialization in AI-related activities mirrors that of
regional specialization in IT. However, foreign-born and native-born workers within the sector
tend to cluster in different locations. Whereas specialization of the foreign-born in AI-related jobs
is strongest in high-tech hubs with a preponderance of private-sector employment, native-born
specialization in AI-related jobs is strongest in centers for military and space-related research.
Nationally, foreign-born workers account for 55% of job growth in AI-related occupations since
2000. In regression analysis, I find that US commuting zones exposed to a larger increases in the
supply of college-educated immigrants became more specialized in AI-related occupations and
that this increased specialization was due entirely to the employment of the foreign born. My
results suggest that access to highly skilled workers constrains AI-related job growth and that
immigration of the college-educated helps relax this constraint.