A new NBER working paper explores how AI has impacted US jobs. Using Burning Glass data from 2010-2018, authors Daren Acemoglu et al. document a rapid growth in AI-related vacancies, particularly in ‘AI exposed’ establishments. They find the following:

AI exposure is associated with both a significant decline in some skills previously demanded in vacancies and the emergence of new ones.
Task substitution partly drives the recent AI surge, whereby AI automates a subset of tasks formerly performed by labour.
The researchers detect no relationship between AI exposure and overall employment or wages at the industry or occupation level.

The paper shows that job losses from AI are larger than job gains in firms that have so far adopted AI. Nevertheless, the aggregate impact is still too small to have had first-order impacts on US employment patterns.

Data

Burning Glass collects data from roughly 40,000 company websites and online job boards. The vacancy data includes occupation, industry and region information, firm identifiers, and detailed information on skills required by vacancies. This is all garnered from the text of the job posting. The Burning Glass data closely tracks overall vacancies in the BLS Job Openings and Labour Turnover Survey (JOLTS).

The authors collect data on vacancies by firm name, location, and industry code (each firm is classified according to the industry in which it posts the most vacancies over the sample period). Within this sub sample, they look at vacancy details relating to skills and occupations. They create two measures of AI vacancies: a narrow one that includes skills relating to AI tasks, and a broad one that uses ‘skill clusters’ relating to AI tasks.[1] Both measures highlight a rapid uptick in AI vacancies since 2016 (Chart 1).