Jobs are changing fast. AI tools can now write, analyse, and make decisions that used to need a person. But not every worker faces the same level of risk. Some jobs are highly exposed, while others are much safer. This article looks at who is most likely to be affected, which skills still matter, and what it all means for workers in Australia.
Each bar shows the estimated probability that a job could be automated by AI. Scores come from Frey & Osborne’s (2017) landmark Oxford study, which analysed 702 occupations. A score closer to 1 means the job is highly at risk. Hover over any bar for details.
Key takeaway: Data entry and telemarketing jobs sit above 99% automation probability. Meanwhile surgeons, nurses and teachers are below 1%. The gap is striking and it comes down to whether a job can be broken into a set of fixed, repeatable steps.
Each bubble is a country. The further right, the more prepared it’s for AI. The higher up, the more jobs are at risk. Bigger bubbles mean a larger share of the workforce is in high-risk occupations. Source: Oxford Insights Government AI Readiness Index 2023; OECD Employment Outlook 2023. Hover for details.
Key takeaway: Australia scores 63.5 out of 100 on AI readiness,solid but not leading. Around 28% of Australian workers are in jobs with high automation risk. Countries like Nigeria and Indonesia face a harder situation,more workers at risk and far less government capacity to respond.
The World Economic Forum’s Future of Jobs Report 2023 surveyed over 800 companies across 27 industries. This heatmap shows the share of companies reporting declining demand for each skill type across sectors. Darker red = faster decline. Hover for exact values.
Key takeaway: Data entry and clerical admin skills are being cut across almost every industry. Finance and legal sectors are moving fastest. Healthcare is the most cautious,human judgment still matters more there than anywhere else.
Real figures tracking global private AI investment (Stanford AI Index 2024), growth in AI-related job postings (LinkedIn Economic Graph 2023), and estimated workers displaced by automation (McKinsey Global Institute 2023). Click legend items to show or hide each line.
Key takeaway: Global AI investment nearly doubled from 2017 to 2023, reaching USD $103 billion. At the same time, AI-related job postings grew by almost 200%. But the number of workers displaced by automation also grew, from under 1 million to nearly 7 million. Investment and opportunity are rising together with disruption.
Each bubble represents Australian workers grouped by education level. Bubble size shows the number of workers in that group. Colour shows median weekly earnings. Automation exposure scores are drawn from OECD (2023) analysis applied to ABS qualification categories. Hover for details.
Key takeaway: The 862,000 Australians with no formal qualification face an 83% automation exposure score, the highest of any group. Workers with postgraduate degrees sit at just 26%. Education is one of the strongest protections available, but over 2 million Certificate III/IV holders still face moderate risk, and they make up the largest single workforce group in Australia.
AI is not replacing every job,it’s replacing specific tasks. Jobs built around processing information, answering routine questions, or following fixed steps are most at risk. Jobs that need empathy, creativity, or hands-on skill in changing environments are much safer.
For Australia, the challenge is not just about technology,it’s about fairness. The workers most exposed to AI are also the least likely to have access to retraining programs. If nothing changes, the gap between high-skill and low-skill workers will keep widening.
The good news is that the window to act is still open. Investing in vocational education, reskilling, and digital literacy now could make the difference between a fair transition and a painful one.
References
Australian Bureau of Statistics. (2023). Average weekly earnings, Australia (Cat. No. 6302.0). https://www.abs.gov.au/statistics/labour/earnings-and-working-conditions/average-weekly-earnings-australia
Australian Bureau of Statistics. (2023). Education and work, Australia (Cat. No. 6227.0). https://www.abs.gov.au/statistics/people/education/education-and-work-australia
Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation? Technological Forecasting and Social Change, 114, 254–280. https://doi.org/10.1016/j.techfore.2016.08.019
LinkedIn. (2023). Jobs on the rise 2023: LinkedIn economic graph. https://economicgraph.linkedin.com/research/jobs-on-the-rise
McKinsey Global Institute. (2023). The economic potential of generative AI: The next productivity frontier. https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai
OECD. (2023). OECD employment outlook 2023: Artificial intelligence and the labour market. OECD Publishing. https://doi.org/10.1787/08785bba-en
Oxford Insights. (2023). Government AI readiness index 2023. https://oxfordinsights.com/ai-readiness/ai-readiness-index/
Stanford HAI. (2024). Artificial intelligence index report 2024. Stanford University Human-Centered Artificial Intelligence. https://aiindex.stanford.edu/report/
World Economic Forum. (2023). The future of jobs report 2023. https://www.weforum.org/reports/the-future-of-jobs-report-2023