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St Albans, UK · POP — · EMP 72,877 · DATA GRADE B

St Albans, UK

36.1 /100

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

#3 of 125

more exposed than 98% 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]
Functional Managers and Directors 6,727
41.1
Information Technology Professionals 3,141
51.2
Sales, Marketing and Related Associate Professionals 2,913
47.3
Teaching and other Educational Professionals 3,670
30.1
Finance Professionals 2,008
53.4
Other Administrative Occupations 1,523
58.9
Sales Assistants and Retail Cashiers 2,317
37.5
Business, Research and Administrative Professionals 1,893
45.7
Secretarial and Related Occupations 1,545
53.1
Managers and Proprietors in Other Services 2,499
32.7

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