Abstract
This study investigates the impact of automation on industry-level employment growth—a key dimension of AI-driven economic transformation since late 2022. Using employment data from 2021 and automation probability estimates from 2023, we examine the relationship between employment growth and automation likelihood across industries. On average, a 10-percentage-point increase in the probability of automation is associated with a 0.52% decline in employment. Further analysis, normalizing employment change by automation probability, reveals substantial heterogeneity across sectors. For instance, community and social service occupations exhibit limited sensitivity to automation (1.87%), while office and administrative support occupations experience a more pronounced decline (-0.04%). Additionally, a cross-industry comparison of robot adoption and job displacement from 2013 to 2023 shows a positive correlation between the two, particularly in manufacturing, logistics, and healthcare. These findings highlight the sector-specific nature of automation’s labor market effects and offer insights into workforce adjustment in an increasingly automated economy.
How to Cite:
, E. & , L.,
(2025) “Measuring the Impact of Automation on Industry-Level Employment Growth”,
Journal of Student-Scientists' Research 7(1).
doi: https://doi.org/10.13021/jssr2025.5199
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