As generative AI instruments develop into extra broadly used, a key difficulty is the know-how’s influence on labor demand. The place would possibly we discover proof of that influence? On this publish, we study whether or not early proof of AI’s impact on the labor market seems in corporations’ job postings. We mix an occupational measure of AI publicity with detailed U.S. job-posting information from Lightcast, which aggregates listings from firm profession pages, nationwide and native job boards, and job-listing aggregators. Utilizing this information, we take a look at whether or not postings for AI-exposed occupations declined disproportionately for the reason that launch of ChatGPT in late 2022. We discover that, whereas general hiring has slowed since then, the proof from job postings offers little indication of a definite AI-driven decline in labor demand.
Measuring a Job’s Publicity to AI
To measure how uncovered totally different jobs are to AI, we use a task-level AI publicity metric developed by Anthropic that mixes detailed activity descriptions from O*NET with noticed AI utilization. O*NET breaks every occupation right into a set of particular actions that staff frequently carry out. For instance, a copywriter could edit or rewrite advertising textual content, whereas an online developer could write supporting code for web sites and net functions. The Anthropic measure evaluates every activity and assigns it an AI publicity rating based mostly on three elements: whether or not the duty might theoretically be principally accomplished by AI; whether or not the duty really seems in a pattern of AI utilization information; and whether or not AI is used to automate the duty moderately than increase it.
Duties obtain the next AI publicity rating if a lot of the noticed utilization is used to automate, moderately than increase, work. These task-level scores are then aggregated to the occupation stage utilizing data on how a lot time staff spend on every activity, producing an occupation-level measure of publicity to AI on a scale from 0 to 1.
This measure needs to be interpreted because the potential AI publicity of an occupation based mostly on noticed utilization. A job being uncovered to AI could not translate into lowered hiring or elevated layoffs for the occupation as a complete; within the New York Fed’s Second District, considerably extra corporations report retraining staff in AI-exposed occupations than lowering hiring. In apply, even when many duties inside an occupation are extremely uncovered to AI, a single activity could restrict the extent to which the occupation as a complete might be automated.
Utilizing this measure of an occupation’s publicity to AI, the chart under compares the distribution of AI publicity throughout occupations in employment (blue) and in job postings (gold). Every bar reveals the share of staff or vacancies in occupations inside a given vary of AI publicity. Shifting proper alongside the x-axis corresponds to occupations with larger publicity, whereas the y-axis stories the share of employment or postings in these publicity bins.
AI Publicity Stays Restricted in Each Employment and Vacancies
Notes: Bars present the share of whole employment in 2024 (blue) and vacancies from January 2026 (gold) throughout occupations grouped by ranges of AI publicity. (The darkish inexperienced is the place the 2 overlap.) The x-axis stories bins of AI publicity, and the y-axis stories the share of employment or vacancies inside every bin.
The chart highlights that AI publicity stays comparatively restricted. Solely a small share of employment or vacancies is concentrated in occupations with excessive AI publicity—lower than 10 p.c of staff and vacancies are in occupations with an AI publicity of at the very least 0.4—and 40 p.c of staff are in jobs with zero measured AI publicity. Given this restricted publicity, will we see any influence of AI once we take a look at the change in job postings over time?
To look at whether or not AI is affecting labor demand, we conduct an occasion examine that compares how job postings evolve for occupations with comparatively excessive versus low AI publicity across the launch of ChatGPT in late 2022. Right here, we outline high-exposure occupations as these with an AI publicity of at the very least 0.2; the outcomes are comparable underneath various cutoff values.
The chart under plots the estimated distinction in job postings between these high-exposure occupations and less-exposed occupations for every quarter relative to the final interval previous to the discharge of ChatGPT (the distinction in 2022:Q3 is zero by building). The blue line within the chart reveals how far more (or much less) hiring occurred in high-exposure occupations in contrast with low-exposure occupations at every cut-off date, relative to the quarter earlier than ChatGPT was launched. The shaded space depicts statistical uncertainty round these estimates. This occasion examine additionally accounts for persistent variations throughout occupations (since some jobs constantly have extra postings than others) and economy-wide adjustments in hiring over time, permitting us to concentrate on variations in hiring by AI publicity.
Declines in Vacancies for AI-Uncovered Occupations Started Earlier than the Launch of ChatGPT in Late 2022
Notes: Occupations are labeled as “excessive publicity” if they’ve a job-level publicity of at the very least 0.2. Occupation weights are derived from the variety of vacancies for that occupation in 2019. The vertical pink line signifies the quarter of ChatGPT’s first public launch. Shaded areas point out 95 p.c confidence intervals.
If AI had had a big causal impact on employment, we’d count on the employment distinction between uncovered and fewer uncovered occupations to behave within the following two methods. First, previous to ChatGPT’s launch, hiring tendencies in high- and low-exposure occupations would transfer equally. This may recommend that, within the absence of AI, the 2 teams would have continued evolving equally. Within the chart, this is able to correspond to estimates being statistically indistinguishable from zero in all quarters previous to 2022:Q3. Second, a sustained divergence between high- and low-exposure occupations ought to emerge sooner or later after ChatGPT’s launch. A niche that opens up—and particularly one which grows over time—could be in step with AI affecting labor demand.
Whereas the chart reveals a relative decline in postings for occupations with larger AI publicity, the occasion examine signifies that this pattern predates the discharge of ChatGPT. The divergence between high- and low-exposure occupations started earlier than 2022 and doesn’t present a transparent further break in trajectory after 2022. In addition to, the hole in labor demand between high- and low-exposure jobs stabilizes after 2023, at odds with AI step by step displacing uncovered occupations. This makes it tough to interpret the relative decline in hiring in AI-exposed occupations as a direct consequence of AI adoption.
Is AI Lowering Demand for Entry-Stage Jobs?
A lot of the early dialogue about AI’s labor-market results has centered on youthful and entry-level staff. Analysis on the employment influence of AI has discovered a bigger decline within the variety of youthful staff in occupations with excessive AI publicity after the discharge of ChatGPT. On the similar time, associated work utilizing job postings finds that demand for junior and senior roles in these occupations declined at roughly the identical time and by comparable magnitudes starting in 2022.
We conduct one other occasion examine to measure the distinction in postings between junior and senior roles inside occupations with excessive AI publicity, relative to late 2022 (proven within the chart under). Values above zero point out that postings for junior roles elevated relative to these for senior roles inside the similar high-AI-exposure occupation, whereas values under zero point out the other. For instance, if the road remained constantly above the horizontal axis after 2022, it will recommend that labor demand for junior positions in high-AI-exposure occupations had grown relative to hiring for senior roles in those self same occupations.
No Clear Divergence in Labor Demand Between Junior and Senior Positions in Occupations with Excessive AI Publicity
Notes: Occupations are labeled as “excessive publicity” if they’ve a job-level publicity of at the very least 0.2. Job postings are categorized as both “junior” or “senior” stage by Lightcast based mostly on data within the posting. Occupation weights are derived from the variety of vacancies for that occupation in 2019. The vertical pink line signifies the quarter of ChatGPT’s first public launch. Shaded areas point out 95 p.c confidence intervals.
If AI have been disproportionately lowering demand for entry-level work, we’d count on the road to maneuver downward after 2022, indicating a relative decline in postings for junior roles. As an alternative, the road fluctuates, with out a clear upward or downward pattern. This means that labor demand for junior and senior roles inside extremely uncovered occupations is shifting broadly in parallel, and that the slowdown in postings will not be concentrated particularly in entry-level extremely uncovered jobs.
Conclusion
General hiring has slowed since 2022, and unemployment has elevated amongst younger staff and up to date school graduates. The proof from job postings means that whereas AI could also be contributing to current labor market developments, it isn’t the primary driver of the slowdown in hiring. In keeping with this interpretation, the New York Fed’s enterprise surveys point out that, to date, corporations intend to include AI primarily by way of retraining, with restricted results on hiring. Whereas job postings present a relative decline in vacancies in occupations with better publicity to AI, that divergence started earlier than the discharge of ChatGPT in late 2022. Furthermore, we don’t observe a divergence in labor demand between junior and senior positions inside extremely uncovered occupations. These patterns make it tough to attribute the current slowdown in entry-level hiring to AI alone.
Richard Audoly is a analysis economist within the Federal Reserve Financial institution of New York’s Analysis and Statistics Group.
Miles Guerin is a analysis analyst within the Federal Reserve Financial institution of New York’s Analysis and Statistics Group.
Giorgio Topa is an financial analysis advisor within the Federal Reserve Financial institution of New York’s Analysis and Statistics Group.
How you can cite this publish:
Richard Audoly, Miles Guerin, and Giorgio Topa, “Do Job Postings Present Early Labor‑Market Results of AI?,” Federal Reserve Financial institution of New York Liberty Avenue Economics, Could 14, 2026, https://doi.org/10.59576/lse.20260514
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Disclaimer
The views expressed on this publish are these of the writer(s) and don’t essentially replicate the place of the Federal Reserve Financial institution of New York or the Federal Reserve System. Any errors or omissions are the accountability of the writer(s).
