CopeCheck Cities scores urban areas on a 0–100 vulnerability index based on workforce composition. Cities with high concentrations of workers in automatable sectors — retail, admin, manufacturing, finance, logistics — score higher. The model uses sector-level automation probabilities derived from Frey & Osborne (2013) and official workforce data (ONS, BLS, CSO Ireland, Statistics Canada, ABS, Stats NZ). It's a blunt instrument, but it shows which local economies have the most to lose.
52 cities ranked by AI displacement vulnerability, based on ONS workforce composition data and Frey & Osborne automation probabilities.
50 cities — one per state — ranked by AI displacement vulnerability, based on BLS workforce composition data and Frey & Osborne automation probabilities.
15 cities ranked by AI displacement vulnerability, based on CSO Census 2022 workforce data and Frey & Osborne automation probabilities.
15 cities ranked by AI displacement vulnerability, based on Statistics Canada employment data and Frey & Osborne automation probabilities.
15 cities ranked by AI displacement vulnerability, based on ABS 2021 Census workforce data and Frey & Osborne automation probabilities.
13 cities ranked by AI displacement vulnerability, based on Stats NZ Census data and Frey & Osborne automation probabilities.
Each city's workforce is broken down by SIC sector. Each sector is assigned an automation risk weight between 0.0 (no risk) and 1.0 (near-certain automation) based on the Oxford/ONS framework. The city's vulnerability score is the employment-weighted average of these sector risks, normalised to 0–100. A score of 100 would mean every worker is in a maximally automatable role. A score of 0 would mean complete insulation. In practice, scores cluster between 45 and 65.
Sector risk tiers: HIGH Admin & Support, Retail, Manufacturing, Financial Services, Transport & Storage MEDIUM Wholesale, Info & Comms, Accommodation & Food LOW Health, Education, Construction, Agriculture, Public Admin, Arts