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Powys, UK · POP — · EMP 61,730 · DATA GRADE B

Powys, UK

29.1 /100

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

#122 of 125

more exposed than 3% 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 2,700
37.5
Agricultural and Related Trades 4,888
18.3
Other Administrative Occupations 1,429
58.9
Caring Personal Services 3,774
20.6
Secretarial and Related Occupations 1,175
53.1
Teaching and other Educational Professionals 1,962
30.1
Administrative Occupations: Finance 993
53.6
Production Managers and Directors 1,380
36
Road Transport Drivers 1,925
24.3
Functional Managers and Directors 1,130
41.1

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