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King's Lynn and West Norfolk, UK · POP — · EMP 69,224 · DATA GRADE B

King's Lynn and West Norfolk, UK

29.4 /100

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

#120 of 125

more exposed than 5% 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 3,672
37.5
Other Administrative Occupations 1,634
58.9
Caring Personal Services 4,215
20.6
Secretarial and Related Occupations 1,557
53.1
Production Managers and Directors 1,833
36
Road Transport Drivers 2,385
24.3
Functional Managers and Directors 1,378
41.1
Sales, Marketing and Related Associate Professionals 1,196
47.3
Managers and Directors in Retail and Wholesale 1,288
43.1
Administrative Occupations: Finance 988
53.6

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