Stoke-on-Trent, UK · POP — · EMP 112,573 · DATA GRADE B

Stoke-on-Trent, UK

29 /100

ILO GenAI exposure index via empirical SOC2020↔ISCO crosswalk · 3-digit data — own scale, not comparable with US/Canada

#123 of 125

more exposed than 2% of UK areas (England & Wales)

Secondary measures

Scenario: if replacement-level AI arrives in 2030

2027 2035

Figure 1. Modeled displacement under the median preset (diffusion k=0.8, ceiling 0.75, automation share 0.45, friction lag 1.5y, attrition 3%/y). Solid: positions eliminated. The gap between gross and layoffs is natural attrition — speed of diffusion, not depth of exposure, determines layoffs. This is a scenario, not a forecast: adjust every assumption.

Where the losses land — and your assumptions

Positions eliminated by 2035 per occupation group, under the arrival year selected above. Drag any multiplier if you think we're wrong about a group — your model, your numbers. Multipliers scale that group's task exposure (×0 = immune, ×2 = double).

Table 3. Group exposure = employment-weighted mean task exposure (Eloundou β over the group's local occupations). Bars use the same scenario engine as Figure 1 (median preset).

Most exposed local occupations

OccupationJobsMedian wageExposure [range]
Sales Assistants and Retail Cashiers 6,816 —
37.5
Caring Personal Services 9,404 —
20.6
Road Transport Drivers 6,262 —
24.3
Other Administrative Occupations 2,492 —
58.9
Customer Service Occupations 2,457 —
50.3
Secretarial and Related Occupations 1,859 —
53.1
Administrative Occupations: Finance 1,824 —
53.6
Elementary Storage Occupations 7,029 —
13.7
Sales, Marketing and Related Associate Professionals 1,924 —
47.3
Managers and Directors in Retail and Wholesale 1,794 —
43.1

Table 2. Ranked by exposure × local employment. Bands on the 0–100 occupation scale.