AI Job Atlas
AI & jobs · Unitary Authority in United Kingdom

Southend-on-Sea

Unitary Authority GB-SOS Largest city: Southend-on-Sea
38%
of jobs here are estimated to be exposed to generative AI, above the national 37% (+1.6 pts).
MODEL12th of 232 regions27.5K exposed workers

Key numbers

PopulationWIKIDATA
160K
as of 2011
Share of national populationWIKIDATA
0.2%
156th largest of 232
People in workMODEL
71.7K
national total × population share
Highest-exposure jobsMODEL
6.7%
national 6.3%
Area
44 km²
3,642 people per km²
Settlement patternMODEL
Highly urban
100% live in major cities
Largest city
Southend-on-Sea
618K (metro)
Mapped towns & cities
1
Natural Earth places

AI use

The Anthropic Economic Index does not publish usage for this region. Regions below a minimum number of sampled conversations are left out.

Sector mix

MODEL

Estimated share of jobs by sector, against the national mix.

Southend-on-Sea United Kingdom
Business services 21.1%
Health & care 12.6%
Retail & wholesale 8.9%
ICT & software 8.9%
Education 8.0%
Public admin 8.0%
Finance 7.2%
Manufacturing 6.0%
Construction 4.9%
Other services 4.9%
Hospitality 4.3%
Transport & logistics 4.0%
Utilities 1.0%
Mining 0.2%
Agriculture 0.2%

Exposed workers by sector

MODEL
Business services 6,108 Health & care 3,808 ICT & software 2,748 Public admin 2,677 Education 2,676 Finance 2,662 Retail & wholesale 2,165 Manufacturing 1,043

Ranking in United Kingdom

MODEL

By modelled AI exposure, out of 232 regions.

9Birmingham 38% 10Bristol 38% 11Glasgow 38% 12Southend-on-Sea 38% 13Plymouth 38% 14Cardiff 38% 15Nottingham 38%
About these estimates. No source publishes AI exposure by region for every country. The model splits United Kingdom's real ILO sector employment across regions using population (Wikidata) and density: denser, capital-city regions get more finance, ICT and professional jobs, and rural regions more farming. Totals match national figures. AI usage figures are measured, not modelled. Methodology

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