Working Paper

AI and Coder Employment: Compiling the Evidence

Abstract: We evaluate whether LLMs have had any discernible impact on the aggregate labor market so far. We focus on occupations that are computer programming-intensive, motivated by data showing that coding is one of the most LLM-exposed tasks. Linking O*NET to CPS we find that aggregate employment of coders has decelerated sharply since the introduction of ChatGPT. Using a novel control variable for industry-level shocks we show that the deceleration is not attributable to the exposure of coders to slowing industries, suggesting instead that coders experienced an occupation-specific shock around the introduction of ChatGPT. Coder employment has continued to grow in recent years, though much more slowly than it did pre-2022. We validate the industry-level control variable by examining historical examples of occupations that experienced either occupation-specific or industry-level shocks. We also provide statistics on the agreement rates between different measures of AI exposure.

JEL Classification: J23; J24; O33;

https://doi.org/10.17016/FEDS.2026.018

Bibliographic Information

Provider: Board of Governors of the Federal Reserve System (U.S.)

Part of Series: Finance and Economics Discussion Series

Publication Date: 2026-03-23

Number: 2026-018