The cities best positioned to weather AI-driven workforce displacement across 6 countries.
Not every city is equally exposed to the AI wave. Some have workforce compositions that naturally resist automation — heavy concentrations in healthcare, education, public administration, and sectors where human presence is structurally required. These are the 10 cities across the CopeCheck network with the lowest vulnerability scores. Being 'best positioned' does not mean safe. It means these cities have more runway before the displacement hits at scale.
With a vulnerability score of just 37.6/100, Canberra stands out for its concentration in harder-to-automate sectors. 46.9% of employment sits in health, education, and public administration — sectors where human judgement, physical presence, and institutional inertia provide genuine insulation from near-term AI displacement. Only 18.8% of the workforce is in high-risk automation categories. This does not mean Canberra is immune to change — it means the change arrives more slowly, and the city has more time to adapt than most.
With a vulnerability score of just 47.3/100, Darwin stands out for its concentration in harder-to-automate sectors. 39.5% of employment sits in health, education, and public administration — sectors where human judgement, physical presence, and institutional inertia provide genuine insulation from near-term AI displacement. Only 25.2% of the workforce is in high-risk automation categories. This does not mean Darwin is immune to change — it means the change arrives more slowly, and the city has more time to adapt than most.
With a vulnerability score of just 48.0/100, Cambridge stands out for its concentration in harder-to-automate sectors. 35.0% of employment sits in health, education, and public administration — sectors where human judgement, physical presence, and institutional inertia provide genuine insulation from near-term AI displacement. Only 24.8% of the workforce is in high-risk automation categories. This does not mean Cambridge is immune to change — it means the change arrives more slowly, and the city has more time to adapt than most.
With a vulnerability score of just 48.2/100, Ottawa stands out for its concentration in harder-to-automate sectors. 36.2% of employment sits in health, education, and public administration — sectors where human judgement, physical presence, and institutional inertia provide genuine insulation from near-term AI displacement. Only 23.8% of the workforce is in high-risk automation categories. This does not mean Ottawa is immune to change — it means the change arrives more slowly, and the city has more time to adapt than most.
With a vulnerability score of just 48.8/100, Oxford stands out for its concentration in harder-to-automate sectors. 37.0% of employment sits in health, education, and public administration — sectors where human judgement, physical presence, and institutional inertia provide genuine insulation from near-term AI displacement. Only 26.4% of the workforce is in high-risk automation categories. This does not mean Oxford is immune to change — it means the change arrives more slowly, and the city has more time to adapt than most.
With a vulnerability score of just 49.1/100, Wellington stands out for its concentration in harder-to-automate sectors. 35.9% of employment sits in health, education, and public administration — sectors where human judgement, physical presence, and institutional inertia provide genuine insulation from near-term AI displacement. Only 25.2% of the workforce is in high-risk automation categories. This does not mean Wellington is immune to change — it means the change arrives more slowly, and the city has more time to adapt than most.
With a vulnerability score of just 50.0/100, Victoria stands out for its concentration in harder-to-automate sectors. 35.5% of employment sits in health, education, and public administration — sectors where human judgement, physical presence, and institutional inertia provide genuine insulation from near-term AI displacement. Only 25.9% of the workforce is in high-risk automation categories. This does not mean Victoria is immune to change — it means the change arrives more slowly, and the city has more time to adapt than most.
With a vulnerability score of just 51.5/100, Hobart stands out for its concentration in harder-to-automate sectors. 36.9% of employment sits in health, education, and public administration — sectors where human judgement, physical presence, and institutional inertia provide genuine insulation from near-term AI displacement. Only 28.5% of the workforce is in high-risk automation categories. This does not mean Hobart is immune to change — it means the change arrives more slowly, and the city has more time to adapt than most.
With a vulnerability score of just 53.4/100, Dunedin stands out for its concentration in harder-to-automate sectors. 35.5% of employment sits in health, education, and public administration — sectors where human judgement, physical presence, and institutional inertia provide genuine insulation from near-term AI displacement. Only 30.2% of the workforce is in high-risk automation categories. This does not mean Dunedin is immune to change — it means the change arrives more slowly, and the city has more time to adapt than most.
With a vulnerability score of just 53.7/100, Townsville stands out for its concentration in harder-to-automate sectors. 36.1% of employment sits in health, education, and public administration — sectors where human judgement, physical presence, and institutional inertia provide genuine insulation from near-term AI displacement. Only 29.8% of the workforce is in high-risk automation categories. This does not mean Townsville is immune to change — it means the change arrives more slowly, and the city has more time to adapt than most.
Rankings are based on CopeCheck's vulnerability index, which scores cities 0–100 using sector employment shares weighted by Frey & Osborne automation probabilities. Lower scores indicate greater natural protection to AI-driven workforce displacement. Data sources: ONS (UK), BLS (US), CSO (Ireland), Statistics Canada, ABS (Australia), Stats NZ (New Zealand).