Ratio Working Paper No. 393: What is an AI Worker? Evidence from Matched Vacancy-Hires

Despite growing policy interest in AI workforce development, surprisingly little is known about what defines these workers, or indeed if they differ from their occupational peers. Using a novel matched vacancy-hire dataset linking Swedish job postings to the individuals hired to fill them, drawn from register data on the entire Swedish population, I study the characteristics of workers who develop and apply AI. Observable traits including high cognitive ability, a tertiary degree in STEM subjects, and a recent migrant background largely explain occupational sorting. Of these, only higher education, prior AI experience, and a science degree set them apart within occupation. I then use earnings as a window onto unobservable differences: AI workers earn approximately 5% more than their peers, entirely explained by firm-level wages. However, AI workers with a doctorate degree stand out sharply in both traits and earnings, indicating that AI workers split into segments that differ by the complexity of their skills and tasks. Taken together, these results point to two distinct policy levers: the supply of average AI workers, termed AI integrators, can be expanded via STEM education participation, while the elite AI developers are supplied by researchers moving to the private sector.

Hellsten, M. (2026). What is an AI Worker? Evidence from Matched Vacancy-Hires. Ratio Working Paper No. 393.