How is AI reshaping the Australian workforce? This tool maps real-world AI adoption across 1,024 occupations, combining observed AI usage patterns from Massenkoff & McCrory's 2026 study with Australian task classifications and workforce data from the ABS. Search any role to see which tasks AI can automate, which it can augment, and how much of the working day is exposed.
Each of the 1,024 ANZSCO occupations is broken into its constituent work tasks, with the proportion of time workers spend on each. Each task is then matched against ~2 million real Claude conversations (Aug–Nov 2025) to see whether AI has demonstrated the ability to help with it. A score of 50% means tasks making up roughly half the role's working day are ones where AI can assist today — not that half the job is already automated, but that the capability exists based on how people are actually using AI elsewhere.
Australian occupation and task definitions come from the ANZSCO classification with task time allocations from ABS. AI penetration scores come from Anthropic's Economic Index, matched to Australian tasks via semantic analysis. Workforce demographics are from ABS Occupation Profiles (Nov 2025). Theoretical baselines from Eloundou et al. (2023). See full methodology.
Click any occupation for a plain-English assessment and full task-by-task breakdown showing how much of the role's time each task takes and whether AI is automating it (doing the work) or augmenting it (assisting the worker). The thin bar below some occupations shows theoretical automation potential — the gap between what AI could do and what it is doing. Higher exposure ≠ job loss — many highly exposed roles are still growing.
Search by job title or ANZSCO code. Click any result for a full assessment.