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Liverpool, UK · POP — · EMP 621,985 · DATA GRADE B

Liverpool, UK

31.6 /100

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

#73 of 125

more exposed than 42% 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 33,584
37.5
Other Administrative Occupations 15,286
58.9
Caring Personal Services 41,609
20.6
Administrative Occupations: Government and Related Organisations 13,103
52.1
Teaching and other Educational Professionals 22,563
30.1
Customer Service Occupations 13,090
50.3
Administrative Occupations: Finance 12,260
53.6
Secretarial and Related Occupations 11,679
53.1
Sales, Marketing and Related Associate Professionals 12,512
47.3
Functional Managers and Directors 14,035
41.1

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