CLANKED

West Berkshire, UK · POP — · EMP 82,307 · DATA GRADE B

West Berkshire, UK

34 /100

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

#19 of 125

more exposed than 86% 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]
Information Technology Professionals 4,044
51.2
Functional Managers and Directors 4,674
41.1
Sales, Marketing and Related Associate Professionals 3,189
47.3
Sales Assistants and Retail Cashiers 3,414
37.5
Other Administrative Occupations 2,047
58.9
Secretarial and Related Occupations 1,840
53.1
Administrative Occupations: Finance 1,651
53.6
Teaching and other Educational Professionals 2,674
30.1
Production Managers and Directors 2,164
36
Finance Professionals 1,368
53.4

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