How AI will reshape Australia’s workforce
Australia’s labour market remains resilient, but employment growth is expected to slow. As AI adoption accelerates, its effects will increasingly shape demand across occupations, with white collar and early-career workers among those most exposed.
Key takeaways
- AI disruption is expected to soften employment demand across 82 occupations, particularly where tasks require less human judgement or interpersonal capability.
- White collar employment growth is forecast to average 1.1% annually over the next five years once AI effects are included, equivalent to around 77,900 fewer jobs than under a scenario without AI effects.
- The trajectory of AI-driven labour market disruption will depend on whether productivity gains justify the costs of implementation and ongoing use.
The Australian labour market has remained relatively resilient over the past three months, adding 102,600 jobs to the economy. However, employment growth is forecast to slow from 1.3% in 2025-26 to 0.9% in 2026-27 as elevated interest rates, weak confidence and global uncertainty weigh on labour demand.
Against this softer outlook, AI is expected to be one of the dominant trends shaping the composition of the labour market. Deloitte Access Economics’ latest Employment Forecasts report outlines which factors will shape the trajectory of AI disruption and how AI is expected to affect different segments of the workforce.
Using Deloitte Human Capital’s Work Analyser tool, Deloitte Access Economics has identified a group of 82 AI-disrupted occupations which are expected to face the greatest risk of softer employment demand, as AI replaces tasks that require less human judgement, empathy or interpersonal skills.
While employment outcomes show little disruption to date, some parts of the Australian workforce are starting to see shifts in hiring patterns, partly reflecting the influence of AI on job tasks and roles. AI-disrupted technology workers are at the forefront of this disruption, with job advertisements for technology occupations more than halving between March 2023 and June 2026.
Evidence of structural labour market disruption due to AI continues to emerge overseas, where adoption of AI is further progressed than Australia.
In the US, employment in the occupations most exposed to AI contracted by 0.2% over the year to June 2026, while employment in the least exposed occupations grew by 1.8%, according to the Stanford Digital Economy Lab. The divergence is more pronounced among early-career workers in the most AI-exposed occupations, whose employment fell by 11.2% between March 2023 and June 2026.
Similar evidence of disruption for early-career workers is appearing in the UK, where the BBC has reported that the number of graduate job vacancies listed in July 2026 has fallen by almost 50% compared to 12 months prior and is at its lowest point since 2016.
As Australia catches up to the leading nations in AI adoption, it is expected that AI will reshape employment outcomes across segments of the workforce in the years ahead.
Overall, white collar workers are expected to experience the greatest disruption from AI implementation, reflecting the concentration of routine tasks performed on computers. Incorporating AI effects into the forecasts is expected to see the average annual growth in white collar employment over the coming five years fall from 1.4% to 1.1%. Compared to the counterfactual scenario without AI effects, this equates to around 77,900 fewer white collar jobs.
By comparison, AI is forecast to provide a modest lift to blue collar and human services employment as productivity gains flow through the wider economy and labour demand shifts between occupations.
However, disruption will not be uniform across white collar work. Administrative and clerical roles are expected to face weaker demand, while occupations in which AI complements human judgement, technical expertise and interpersonal capabilities may benefit. AI could support these workers by automating routine activities, freeing up time and improving the quality of cognitive work.
Increasingly, the cost of AI will be central in determining the pace and extent of AI adoption, and the resulting disruption. Although AI appears to be becoming cheaper, as costs become metred and charged on a per-token basis, many companies are facing an AI spending reality check.
These cost pressures are likely to make adoption selective and uneven. Businesses will need to determine whether the productivity gains from AI justify the cost of implementation and ongoing use, directing investment towards the tasks and workflows that offer the strongest commercial return. As a result, firms and workers who can navigate these dynamics will likely harness the full potential of the technology and drive transformation across the labour market.
