Artificial intelligence is a source of concern for Australians. Is the fear, however, grounded on reality? New information from Skills and Jobs Surveys of trust conducted in Australia, the OECD, and throughout the world reveal a startling discrepancy: people with the least to fear are frequently the most concerned, and the jobs that Australians fear losing are not typically the ones that are most at risk.

Chart 1: How Worried Are Australians About AI Job Loss?

Australian employee anxiety about job displacement from key economic threats, 2023–2025 (% reporting concern)
Source: Edelman Trust Barometer Australia (2024, 2025), Survey of ~1,100+ Australian adults per year. “Automation / AI” reflects concern about job displacement from automation. humanities.org.au (2025).

Chart 2: Which Occupations Face the Highest AI Exposure?

Gen AI automation exposure score by occupation group, Australia (score 0–1, where 1 = fully automatable)
Source: Jobs and Skills Australia (2025). (Our Gen AI Transition: Exposure) Exposure scores derived from ILO framework,(Gmyrek, Berg & Bescond, 2023) adapted to ANZSCO occupational classifications using ABS Census 2021 data.

Chart 3: Risk, Reward, and the Size of the Problem

Automation exposure score vs. median weekly earnings vs. number of workers — a multivariate view of who’s in the firing line
Source: Jobs and Skills Australia (2025). Our Gen AI Transition; ABS (2024). Employee Earnings and Hours, Australia; ABS (2024). Labour Force, Australia. Worker counts are approximate based on Census 2021 employment data. Earnings are approximate median weekly full-time ordinary time earnings by occupation group.

Chart 4: Who Bears the Burden? A Multivariate Risk Profile

Gen AI automation exposure by gender, age group, and education level — a heatmap of vulnerability
Source: Derived from Jobs and Skills Australia (2025). Our Gen AI Transition; ABS (2024). Labour Force Survey; ABS Census (2021). Average automation exposure scores are estimated by applying JSA occupation-level exposure scores to workforce composition by age, gender, and education within each occupation group. Values are illustrative of the directional patterns in the underlying data.

Chart 5: The Mismatch — Fear vs. Actual Displacement

Australian employee concern about AI job loss (%) vs. actual AI-attributable job displacement (% workforce) — the gap between anxiety and evidence
Source: Edelman Trust Barometer Australia (2025); Deloitte Access Economics (June 2026). Employment Forecasts: The Year of AI; PwC (2025). AI Jobs Barometer Australia; ABS (2024). Labour Force, Australia. Worker concern percentages are group-level estimates derived from survey data on AI job displacement anxiety by occupation type. Actual displacement figures reflect Deloitte’s modelled estimates of AI-attributable employment decline across 82 high-risk occupations as of mid-2026.

Story Pitch

The Automation Anxiety Gap: Who’s Really at Risk from AI in Australia?

Although the research reveals a more complex picture than the headlines suggest, Australians are concerned about AI. This graphic tale reveals a startling discrepancy between fear and reality using the most recent Australian government statistics (Jobs and Skills Australia’s Our Gen AI Transition, 2025) and the Deloitte Access Economics Employment Forecasts released just days ago (June 2026). The employees who are most likely to experience job disruptions—such as general clerks, receptionists, and accounting assistants—are not the ones who voice their concerns the loudest. Managers and professionals, who are exposed to significantly less automation, frequently exhibit the highest levels of worry. The highest-risk jobs are disproportionately occupied by women with mid-level skills. Additionally, the structural shift is accelerating even if real AI-attributable displacement has so far been minimal (Deloitte thinks 82 occupations are materially affected).The Australian audience can use this relevant, data-rich, and actually helpful story to evaluate their own circumstances instead of responding to generalized dread. It links state-of-the-art government and business research that most Australians aren’t aware of.

References

Deloitte Access Economics. (2026, June 4). Deloitte Access Economics Employment Forecasts: The year of AI. Deloitte Australia. https://www.deloitte.com/au/en/about/press-room/deloitte-access-economics-employment-forecasts.html

Edelman. (2024). 2024 Edelman Trust Barometer: Australia report. Edelman. https://www.edelman.com/au/trust/2024/trust-barometer

Edelman. (2025). 2025 Edelman Trust Barometer: Australia report. Edelman. https://www.edelman.com/au/trust/2025/trust-barometer

Gmyrek, P., Berg, J., & Bescond, D. (2023). Generative AI and jobs: A global analysis of potential effects on job quantity and quality (ILO Working Paper No. 96). International Labour Organization. https://doi.org/10.54394/FHEM8239

Jobs and Skills Australia. (2025). Our Gen AI transition: Exposure. Australian Government. https://www.jobsandskills.gov.au/studies/generative-artificial-intelligence-capacity-study/our-gen-ai-transition-exposure

Australian Bureau of Statistics. (2024). Labour force, Australia (Cat. No. 6202.0). ABS. https://www.abs.gov.au/statistics/labour/employment-and-unemployment/labour-force-australia

Australian Bureau of Statistics. (2024). Employee earnings and hours, Australia (Cat. No. 6306.0). ABS. https://www.abs.gov.au/statistics/labour/earnings-and-work-hours/employee-earnings-and-hours-australia ```