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  "id": "future-of-work/ai-employment-in-australia/which-australian-jobs-are-most-at-risk-from-ai-a-role-by-role-breakdown",
  "title": "Which Australian Jobs Are Most at Risk from AI? A Role-by-Role Breakdown",
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  "content": "Now I have sufficient data to write a comprehensive, well-cited article. Let me compile it.\n\n---\n\n## Which Australian Jobs Are Most at Risk from AI? A Role-by-Role Breakdown\n\nNot all Australian workers face the same AI disruption risk — and the difference between a data entry clerk and a plumber is not merely anecdotal. It is measurable, occupation-specific, and now documented in authoritative Australian government research. Yet most coverage of AI and jobs defaults to sweeping industry-level claims — \"finance is at risk,\" \"retail will be disrupted\" — without telling the nurse, the bookkeeper, or the call centre agent what that actually means for *their* role on Monday morning.\n\nThis article maps specific Australian occupations onto their AI exposure risk using the most authoritative available frameworks: Jobs and Skills Australia's *Our Gen AI Transition* study, the Barrenjoey investment bank report, the ILO's occupational exposure methodology, and the emerging FutureWork AU dataset built on official Australian Bureau of Statistics and Jobs and Skills Australia figures. The goal is a clear, occupation-specific risk assessment — not a generic industry prediction.\n\n---\n\n## How AI Risk Is Actually Measured for Australian Occupations\n\nBefore examining individual roles, it is worth understanding how researchers arrive at risk scores — because the methodology determines the conclusion.\n\n\nJobs and Skills Australia's landmark *Our Gen AI Transition* study built on the Felten (2021) framework and adapted a method from the International Labour Organization (ILO), tailoring it to the Australian and New Zealand Standard Classification of Occupations (ANZSCO) for a view of generative AI's potential across the Australian labour market.\n\n\n\nEach task within an occupation receives two scores: an *augmentability* score (whether Gen AI could assist or enhance the task) and an *automatability* score (whether Gen AI could fully undertake it). Scores range from 0 to 1, and the spread of scores within each occupation is also examined — meaning researchers can identify whether some tasks within the same job are highly automatable while others are not.\n\n\nA separate Australian dataset — FutureWork AU — scores 358 occupations using four independent data layers: \nAustralian Government employment and education data, a government study on generative AI and job tasks, live job listings from SEEK, and separate assessments from Claude, GPT, Gemini, and Grok. To reduce the impact of any single model, the dataset uses the median score from the four AI systems rather than an average.\n\n\n\nFutureWork AU places Australia's median workforce AI exposure score at 3 out of 10, linking that lower midpoint — compared with economies such as the United States — to the country's larger share of trade, mining, and other physically oriented work.\n\n\n---\n\n## The Core Finding: Most Jobs Change, Few Disappear Entirely\n\nThe single most important finding from the Australian government's own research cuts against the alarmist narrative: \naugmentation generally outweighs automation. Current generative AI technologies are more likely to enhance workers' efforts in completing tasks rather than replace them — especially in high-skilled occupations. The higher potential for automation is concentrated in routine clerical and administrative roles.\n\n\nThat said, the Barrenjoey report presents a more sobering headline: \nthe report found only one in 1,000 Australian jobs will likely remain untouched by technology and AI, marking what it calls the \"most comprehensive workforce transformation\" in modern history.\n And \nBarrenjoey chief economist Jo Masters found that around 11% of Australia's workforce is at heavy risk of being replaced, while 22% face a medium risk of losing their jobs.\n\n\nThe critical distinction — explored in depth in our companion guide *AI and Australian Jobs Explained: Automation vs. Augmentation* — is that \"exposure\" to AI does not automatically mean \"replacement by AI.\" What it does mean is that some roles face a structurally worse combination: high automation exposure *and* limited options to move elsewhere.\n\n\nLabour mobility will shape long-term impacts. Workers' abilities to adapt to changes in their occupations and to transition between occupations will be critical. Some roles face repeated exposure to automation with limited mobility options, highlighting the need for targeted policy responses.\n\n\n---\n\n## High-Risk Occupations: Repeated Exposure with Limited Mobility\n\n### Clerical and Administrative Workers\n\n\nANZSCO skill level 4 — which includes several forms of clerical work — shows the highest automation potential. Many clerical tasks that were not affected by previous waves of automation could now be undertaken in large part by generative AI.\n\n\n\nJobs and Skills Australia found that some roles face \"repeated exposure to automation with limited mobility options.\" Jobs set to lose the most employment by 2050 include office clerks, receptionists, bookkeepers, and professionals in sales, marketing, public relations, business analysis, and programming.\n\n\nWhy is mobility so important here? A data entry clerk whose tasks are automated cannot easily pivot to a nursing role or a construction site — the physical, interpersonal, and credential requirements are entirely different. The automation risk is compounded by a career pathway that offers few adjacent exits.\n\n**Roles in this category and their risk profile:**\n\n| Occupation | Primary AI Risk | Mobility Options |\n|---|---|---|\n| Data Entry Clerk | Very High — core tasks are structured, repetitive text processing | Very Low — narrow skill set with few adjacent roles |\n| General Receptionist | High — scheduling, query handling, information retrieval | Low-Medium — some client-facing roles remain human-preferred |\n| Bookkeeper | High — transaction categorisation, reconciliation, ledger entry | Medium — can pivot to advisory accounting with upskilling |\n| Payroll Officer | High — calculations, compliance checking, report generation | Medium — regulatory knowledge has ongoing value |\n| Office Clerk (General) | Very High — filing, data processing, document management | Very Low — highly substitutable task profile |\n\n\nLabourers, machine operators, sales workers, and general clerks are the jobs most at risk of substitution and obsolescence, according to the Barrenjoey report.\n\n\n### Call Centre Agents and Customer Service Representatives\n\nCall centre roles represent the most visible frontline of AI displacement in Australia — and the most instructive case study in the gap between AI promise and AI reality.\n\n\nThe Commonwealth Bank began testing a generative AI chatbot named \"Hey CommBank\" in late 2024, leading to fears it would replace many of its 2,400 contact centre staff.\n In July 2025, \nthe bank said it could cut 45 call centre jobs thanks to customer-facing chatbots, which it asserted cut call volume by 2,000 calls a week. It later admitted that artificial intelligence did not actually cut down the number of customers needing to speak to a human. The bank's plan \"did not adequately consider all relevant business considerations, and this error meant the roles were not redundant.\"\n\n\n\nCommonwealth Bank of Australia ultimately reversed a decision to cut the 45 customer service roles after pressure from the country's main financial services union.\n\n\nThis episode illustrates a pattern playing out globally: \nseveral companies that shed jobs in favour of AI have later rehired many of the workers they laid off. Swedish fintech Klarna rehired some of its human customer service staff after replacing them with AI chatbots, while tech giant IBM rehired staff after replacing much of its human resources division with AI.\n\n\nThe risk to call centre agents is real but not yet fully realised. The structural pressure — from AI voice bots, automated ticketing systems, and chatbot-first customer service models — is intensifying. Workers in these roles should treat the CBA case not as a reprieve, but as a warning about the direction of travel.\n\n### Checkout Operators and Retail Sales Assistants\n\n\nThe Barrenjoey research reveals that consumer staples retail has the highest substitution risk among ASX industries, with more than 125,000 checkout operators and 560,000 sales assistants nationwide still performing tasks that could be automated.\n\n\nSelf-checkout technology is already well-established; AI-powered frictionless checkout (scan-free stores) is the next phase. For checkout operators specifically, the automation risk is high and the mobility options are constrained by geography, education level, and local labour market conditions — factors examined in detail in our guide *Who Is Most Vulnerable to AI Job Displacement in Australia?*\n\n---\n\n## Medium-Risk Occupations: Augmented but Structurally Pressured\n\n### Accounting and Finance Professionals\n\n\nHigh-exposure occupations include a range of tech roles, as well as occupations including accounting, marketing, administrative assistance, and banking and finance.\n However, the risk profile for accountants differs meaningfully from that of bookkeepers. While routine bookkeeping tasks face high automation potential, qualified accountants who provide strategic advice, interpret complex tax law, and manage client relationships are more likely to be augmented than replaced.\n\nThe distinction is task-level, not occupation-level: an accountant who spends 80% of their time on data entry is more exposed than one who spends 80% of their time on strategic planning. AI is reorganising *what* accountants do, not necessarily *whether* accountants exist.\n\n### Legal Support and Paralegal Roles\n\nDocument review, contract summarisation, legal research, and due diligence — the bread and butter of paralegal and junior solicitor work — are precisely the structured, text-based tasks that large language models handle well. Law firms across Australia are already deploying contract-review AI, as covered in our sector analysis *AI's Impact by Industry: How Automation Is Reshaping Finance, Healthcare, Law, and Retail in Australia*. The risk is highest for entry-level legal roles, where junior lawyers and paralegals traditionally built experience through exactly the tasks AI now performs faster and cheaper.\n\n### Marketing Coordinators and Content Producers\n\n\nA Microsoft researcher study also found the jobs most exposed to AI chatbots include interpreters and translators, historians, sales and customer service representatives, and writers and authors.\n Marketing coordinators who produce templated copy, social media posts, and basic campaign briefs face meaningful automation pressure. Those who provide creative strategy, brand direction, and client relationship management are better positioned — but must actively demonstrate that value.\n\n---\n\n## Low-Risk Occupations: Physical Dexterity, Unstructured Environments, Human Presence\n\n### Trades and Construction\n\n\nAn Australian occupational risk map scoring 358 occupations found clerks and telemarketers most exposed, while trades and farming sit at the lower end of the risk scale. Lower-risk roles include construction workers, crop managers, and school principals.\n\n\nThe reason trades resist automation is structural, not incidental. Plumbing, electrical work, carpentry, and bricklaying require fine motor coordination in unpredictable physical environments — a combination that current robotics cannot reliably replicate at commercial scale. A robot that can weld a car chassis in a controlled factory cannot yet navigate the uneven terrain of a residential renovation.\n\n\nAustralia's lower median AI exposure score compared with the US is linked to the country's larger share of trade, mining, and other physically oriented work. Even so, lower exposure does not mean no change — some trade and agricultural occupations already use AI tools in day-to-day work, including crop monitoring in farming.\n\n\n### Nursing, Midwifery, and Aged Care\n\nNursing and personal care roles combine emotional attunement, physical assistance, and clinical judgment in ways that AI cannot replicate. The demand for these roles is also growing — driven by Australia's ageing population — making them among the most structurally secure occupations in the labour market. For a full analysis of why these roles are positioned to grow through 2030, see our guide *Jobs AI Cannot Replace in Australia: The Human-Advantage Roles Set to Grow Through 2030*.\n\n\nAccording to the FutureWork AU dataset, doctors, engineers, and scientists are among the occupations where AI is more likely to assist existing work than replace it.\n\n\n### Hospitality and Food Service\n\nHospitality workers — chefs, baristas, wait staff, hotel concierges — operate in highly variable, sensory, and interpersonal environments. While robotic kitchen assistants and AI-driven ordering systems exist, full automation of a café or restaurant remains technically and commercially unviable at scale in Australia. \nHigher-exposure sectors such as financial services and education are adopting AI at speed, while jobs that combine sector expertise with AI literacy — especially in mining, health, and hospitality — are seeing growth.\n\n\n---\n\n## The Sectors Already Restructuring\n\nThree Australian sectors are already in active workforce restructuring driven at least partly by AI adoption:\n\n**Financial Services:** \nFinancial and Insurance Activities continues to lead in terms of industry demand for AI skills, with 11.8% of job postings in the sector demanding AI skills in 2024.\n \nTelstra has been among the big-name companies admitting that AI will likely see its workforce get smaller in the coming years as the technology outperforms humans in certain roles. It has also mandated every worker to start using AI to see if it can help with certain tasks.\n\n\n**Telecommunications:** Telstra's public acknowledgment that AI will shrink its workforce by 2030, combined with its mandatory AI-use policy for all employees, signals an organisation actively restructuring around AI augmentation — with headcount reduction as an explicit downstream goal.\n\n**Retail:** \nConsumer staples retail has the highest substitution risk among ASX industries, with over 125,000 checkout operators and 560,000 sales assistants performing tasks ripe for automation.\n The structural shift toward self-service and AI-assisted retail is already underway and accelerating.\n\n---\n\n## Key Takeaways\n\n- \n**Automation risk is concentrated in clerical and administrative roles.** Current generative AI technologies are more likely to enhance workers' efforts than replace them in high-skilled occupations, but the higher potential for automation is concentrated in routine clerical and administrative roles.\n\n\n- **The \"repeated exposure with limited mobility\" trap is the real risk.** \nWorkers' abilities to adapt to changes in their occupations and to transition between occupations will be critical. Some roles face repeated exposure to automation with limited mobility options.\n Data entry clerks and general office clerks are the clearest examples.\n\n- \n**The Barrenjoey report found that nearly 10.9% of the workforce faces a high risk of replacement, while 22.3% are at medium risk. Just over 7% of the workforce is highly exposed to augmentation, while an additional 38.4% has medium exposure.**\n\n\n- **Trades, nursing, and hospitality remain structurally low-risk** due to physical dexterity requirements, unstructured environments, and irreplaceable human presence — not because AI won't touch them at all, but because full automation is commercially and technically unviable at scale.\n\n- **Sector restructuring is already underway in finance, telecommunications, and retail** — meaning workers in these industries face near-term, not hypothetical, exposure.\n\n---\n\n## Conclusion\n\nThe question \"will AI take my job?\" cannot be answered at the industry level. It must be answered at the occupation level — and ideally, at the task level within that occupation. A bookkeeper and a strategic CFO both work in finance; their AI risk profiles are almost entirely different.\n\nThe authoritative Australian evidence — from Jobs and Skills Australia, the Barrenjoey report, and the ILO-adapted methodology — points to a labour market that is being reshaped unevenly. Clerical, administrative, and routine customer service roles face the sharpest structural pressure, compounded by limited mobility options. Trades, nursing, and hospitality face the least. And the sectors of financial services, telecommunications, and retail are already restructuring in ways that are making these risk profiles real rather than theoretical.\n\nFor workers in high-risk roles, the most important next step is not panic — it is an honest, task-level audit of what your job actually involves, and whether those tasks are routine and text-based or physical, interpersonal, and judgment-dependent. That audit is the foundation of the upskilling roadmap covered in our guide *How to Future-Proof Your Career Against AI in Australia: A Step-by-Step Upskilling Plan*. And if you're weighing whether to stay in your current field or pivot entirely, the structured decision framework in *Should You Retrain, Pivot, or Stay?* provides a methodology tied directly to your occupation's exposure level.\n\nThe data is clear enough to act on. The question is whether workers will get ahead of the curve — or wait to be caught by it.\n\n---\n\n## References\n\n- Jobs and Skills Australia. *\"Our Gen AI Transition: Implications for Work and Skills.\"* Australian Government, 2025. https://www.jobsandskills.gov.au/publications/generative-ai-capacity-study-report\n\n- Jobs and Skills Australia. *\"Our Gen AI Transition – Exposure.\"* Australian Government, 2025. https://www.jobsandskills.gov.au/studies/generative-artificial-intelligence-capacity-study/our-gen-ai-transition-exposure\n\n- Barrenjoey. *\"AI and the Australian Workforce.\"* Barrenjoey Investment Bank, 2025. (Reported via SBS News, September 2025.)\n\n- PwC Australia. *\"The Fearless Future: How AI is Impacting Australia's Jobs and Workers.\"* AI Jobs Barometer Report, June 2025. https://www.pwc.com.au/services/artificial-intelligence/ai-jobs-barometer-report-2025.pdf\n\n- Indeed Hiring Lab Australia. *\"Nothing Artificial About Australian AI Adoption: Business and Government Trends.\"* Indeed, April 2026. https://www.hiringlab.org/au/blog/2026/04/01/nothing-artificial-about-australian-ai-adoption/\n\n- Gmyrek, P., Berg, J., & Bescond, D. *\"Generative AI and Jobs: A Global Analysis of Potential Effects on Job Quantity and Quality.\"* International Labour Organization (ILO), 2023.\n\n- Information Age / ACS. *\"Aussie Jobs Most Vulnerable to AI Outlined in Govt Study.\"* August 2025. https://ia.acs.org.au/article/2025/aussie-jobs-most-vulnerable-to-ai-outlined-in-govt-study.html\n\n- Baum, S., & Houghton, J. *\"The Time-less Threat of Automation: Has New Technology Been the Predicted Job Killer?\"* *Australian Journal of Political Economy*, 2024. https://www.tandfonline.com/doi/full/10.1080/10301763.2024.2363573\n\n- FutureWork AU / Integral Media. *\"AI Exposure of Australian Occupations — Interactive Dataset.\"* 2026. (Reported via ChannelLife Australia, April 2026.) https://channellife.com.au/story/australia-map-shows-ai-risk-for-clerks-telemarketers\n\n- Bloomberg / American Banker. *\"Commonwealth Bank of Australia Reverses Move to Replace 45 Jobs With AI.\"* August 2025. https://www.bloomberg.com/news/articles/2025-08-21/commonwealth-bank-reverses-job-cuts-decision-over-ai-chatbots",
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