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South Somerset, UK · POP — · EMP 80,932 · DATA GRADE B

South Somerset, UK

30.3 /100

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

#112 of 125

more exposed than 11% 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 4,207
37.5
Other Administrative Occupations 1,892
58.9
Caring Personal Services 4,719
20.6
Sales, Marketing and Related Associate Professionals 1,840
47.3
Secretarial and Related Occupations 1,577
53.1
Functional Managers and Directors 1,907
41.1
Production Managers and Directors 2,001
36
Administrative Occupations: Finance 1,300
53.6
Teaching and other Educational Professionals 2,177
30.1
Managers and Directors in Retail and Wholesale 1,418
43.1

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