Australia's Department of Employment and Workplace Relations has released the first national report on the impact of artificial intelligence on the labor market. My colleagues and I have carefully studied this document. The main conclusion: there is no catastrophic scenario of mass layoffs, but a structural shift is clearly visible — employment in professions most vulnerable to generative AI is growing significantly slower.
According to the data, from November 2022 to February 2026, employment growth in the fifth of professions with the highest exposure to AI was only 5.6%. For comparison, in the group least affected by the technology, this figure reached 9.5%. The difference of 3.9 percentage points is, according to the department, an "early and moderate signal," not evidence of a collapse. My analysis confirms: the market is adapting, but the trend has already emerged.
Who is at risk and why
The analysis shows that routine cognitive professions are primarily affected. This group includes office workers, data entry operators, accountants, advertising and marketing specialists, as well as programmers. Interestingly, the traditional view of automation as a threat to physical labor is outdated. Today, generative models are more effective at replacing intellectual tasks: writing texts, processing data, and preparing documents.
Professions requiring manual labor and personal care are least susceptible to automation: caregivers, electricians, truck drivers, carpenters, and plumbers. Here, the share of men is 69.5%, while in the vulnerable group it is only 43.7%. Additionally, workers with higher education are at risk: 43.7% of them have a bachelor's degree, compared to only 14.9% in the "safe" group. This is because their tasks are easier to automate.
It's not that straightforward
An important nuance: some professions with high exposure to AI continue to grow. For example, the number of software and application developers in Australia reached 199,000 by February 2026 — 25% higher than in November 2022. That is, the technology is not just displacing but also creating new opportunities. The labor market for graduates also remains stable: youth unemployment among those with higher education is low, and the share of those working in their field of study has increased.
At the same time, Australia's unemployment rate in February 2026 was 4.2% — lower than any value in the decade before the pandemic. The employment-to-population ratio reached 64%, above the pre-pandemic average. However, in the group of highly exposed professions, employment, hours worked, and the number of vacancies grew more slowly, while unemployment increased more sharply. The report's authors rightly note that these trends may be linked not only to AI but also to post-pandemic restructuring and macroeconomic factors.
The Australian government, judging by statements from Employment Minister Amanda Rishworth, intends to use AI to create "good jobs, not threats to them." The department plans quarterly monitoring, although the next update is expected only at the end of 2026. Against this backdrop, it is worth recalling the bold statements by Anthropic CEO Dario Amodei about the possible destruction of up to half of entry-level "white-collar" jobs. However, real data from Australia so far refutes apocalyptic forecasts.
My expert conclusion: The Australian report is an important but only first step in understanding the long-term impact of AI. The data shows not so much a catastrophe as a redistribution of labor resources. The market is adapting, but for "white-collar" workers in cognitive professions, the signal is alarming — they will either have to retrain or find niches where the human factor remains irreplaceable.