Where AI is used, hiring has slowed.

Where AI is used, hiring has slowed.

AI is starting to show up in Australia's job ads. We compared job advertisements for occupations where AI is actually being used; jobs like software programmers, analysts and call centre workers, against similar occupations where it isn't, before and after ChatGPT arrived. Since late 2022, the AI-using occupations have been advertising roughly 390 fewer openings a month than their counterparts. That gap is too large to be chance.

How big is that? These occupations normally advertise around 25,000 openings a month. A gap of roughly 390 a month means that for every 100 openings they would normally post, one or two are now missing. For scale, Australia's overall job-ad market fell by about 74,000 ads a month between 2022 and 2025, as post-COVID hiring normalised and interest rates rose. For every job ad linked to AI, the economic cycle removed roughly 190. The AI effect is small but real, and unlike the cycle, it is concentrated in a specific set of occupations.

Two things this finding is not. It is not proof that AI alone caused the gap. These occupations overlap heavily with a tech sector that had its own hiring downturn, and some of the gap predates ChatGPT. It is also not job losses: employment in these occupations has continued growing. The signal is slower hiring, not firing. That is the earliest form a labour-market shift can take, which is exactly why it is worth watching.

WA accounts for roughly one in nine advertised vacancies nationally in our dataset, but appears to hold a smaller share (closer to one in fourteen) of vacancies in the occupations where AI is used. Much of the gap between the two estimates is therefore scale: WA simply has proportionally fewer of these roles. Additionally, a labour market anchored in mining and resources may have less of these AI usage roles, although that needs testing. Where the roles do exist, the slowdown is statistically detectable and consistent in strength with the national one, though it clears a lower evidentiary bar than the national result.

The federal government's first report on AI and employment, released last month by DEWR, points the same way: modest slowing in exposed occupations, no upheaval. Our analysis looks earlier in the pipeline: at hiring rather than headcounts, which is where we would expect the first signs of impact to show up.

Fine print: Difference-in-differences on Internet Vacancy Index data to February 2026. The IVI counts online job advertisements from major recruitment platforms, published as a 3-month moving average, so figures are advertised online vacancies rather than total vacancies, and estimates are relative to the comparison group's trend rather than counts of jobs lost. We compare 14 occupations with observed AI use against occupations predicted to be AI-exposed but with lower observed use, before and after November 2022. National: 391 fewer advertised vacancies per month, p = 0.005. WA: 33 fewer, p = 0.014, robust across our full battery of checks and negative in all 1,000 bootstrap resamples, though not significant under the matched bootstrap, our strictest test. Figures reflect a July 2026 correction to the occupation crosswalk, which strengthened the estimates. This is early evidence: three years of post-ChatGPT data, and the post-COVID hiring correction cannot be fully separated out, and the treated group was already softening from mid-2021.. Observed use is measured from US Claude usage data mapped to Australian occupations via the ONET task taxonomy (Massenkoff & McCrory 2026); it proxies US rather than Australian adoption, and any resulting misclassification biases the estimate toward zero. The July correction bore this out, moving the estimate further from zero. DEWR's AI and Employment in Australia (June 2026) provides the national employment-side benchmark; its job-advertisement model variant, run against predicted exposure, found no significant effect. Source: AITAI Jobs Corpus and Analysis (rev. July 2026).