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Ipswich, UK · POP — · EMP 67,028 · DATA GRADE B

Ipswich, UK

31.1 /100

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

#88 of 125

more exposed than 30% 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 3,970
37.5
Information Technology Professionals 1,895
51.2
Caring Personal Services 4,536
20.6
Other Administrative Occupations 1,546
58.9
Road Transport Drivers 3,077
24.3
Customer Service Occupations 1,439
50.3
Administrative Occupations: Records 1,460
47
Secretarial and Related Occupations 1,139
53.1
Administrative Occupations: Finance 1,102
53.6
Functional Managers and Directors 1,375
41.1

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