RBA analysis finds tentative job weakness for young workers in AI-exposed roles

Young workers appear to be losing ground relative to older colleagues in Australia’s most AI-exposed occupations, according to an analysis published by the Reserve Bank of Australia on November 9, 2026. Author Mike Major describes a tentative warning signal—not proof of AI-driven job losses—and finds little evidence of material disruption across the Australian labor market.

The staff note introduces a monitoring approach designed to catch changes that national employment totals might miss. It combines two views of the workforce: occupations whose tasks are potentially exposed to AI, and young workers and graduates who may encounter changing hiring practices first.

The weakness is concentrated, not uniform

Within the most exposed occupations, younger workers appear to have experienced weaker employment outcomes and larger unemployment increases than older workers. That age pattern does not appear in less-exposed occupations. The data are volatile, but the result also holds when Major restricts the comparison to market-sector occupations.

Other indicators offer a mixed picture rather than a single, consistent signal of falling demand:

• Job advertisements have slowed somewhat more in the most AI-exposed occupations than in other groups.
• Employment growth and total hours worked have been a little weaker in more-exposed occupations in recent years.
• Job-finding rates and movements from employment into unemployment show little difference across exposure groups.

General clerks, software and applications programmers, ICT business and systems analysts, call-center workers and receptionists contributed most to the decline in new job advertisements in the highest-exposure group. That comparison uses Jobs and Skills Australia advertising data from November 2022 onward.

Exposure can mean replacement—or assistance

Major’s exposure rankings use Jobs and Skills Australia’s mapping of occupations to tasks susceptible to AI automation. They measure potential task exposure, not whether businesses have adopted AI or changed hiring and pay decisions. The analysis uses November 2022 as its benchmark because that was when ChatGPT brought generative AI into public use.

Demand for AI-related skills is another moving part. AI keywords have become more common in SEEK and Indeed advertisements. Major cautions that some of the increase may reflect changing language rather than genuinely different skill requirements. Those measures also reveal less about whether demand for other work is being displaced.

A young-worker warning with a data lag

Young people’s outcomes have softened relative to the workforce overall, but conditions remain stronger than before the pandemic. Youth employment is especially sensitive to economic swings. Its strength in 2022 partly reflected an exceptionally tight labor market, so subsequent weakness may reflect cooling conditions rather than AI adoption.

The latest complete occupation data are from February 2026, with partial figures for May. Changes to the Labour Force Survey and occupation classifications mean newer data will need a revised exposure mapping. The November publication therefore does not provide a real-time account of hiring conditions.

Major identifies business surveys and direct contact with firms as important ways to establish whether employers are using AI and how they are responding. That evidence would help connect the task rankings to workplace decisions—the missing link between identifying vulnerable groups and explaining what is happening to them.