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Tier A United Kingdom · 2025

AI Job Risk in United Kingdom - Which Occupations Are Most at Risk?

The short answer: Clerical support workers score 8.5/10 - the highest AI exposure in United Kingdom.

Which jobs are most at risk from AI in United Kingdom? Clerical support workers leads at 8.5/10. Workforce average: 5.1/10. Data covers 34.1M workers. Free. Official government data.

Total Workforce
34.1M
workers tracked
Avg AI Exposure
5.1/10
workforce-weighted
Most Exposed
Clerical support workers
8.5/10
Safest Occupation
Elementary occupations
2.0/10
Informal Employment
19.8%
of workforce (ILO)

All Occupations Ranked by AI Exposure

10 ISCO-08 occupation groups · data year 2025 · Tier A Full data - employment, wages, AI scores, growth projections

ISCO Occupation Group AI Exposure Robotics Risk WFH Potential Employment Median Wage
4 Clerical support workers 8.5/10 2.5/10 8.5/10 3.0M $33,216
2 Professionals 6.5/10 1.5/10 7.5/10 8.6M $57,473
1 Managers 5.5/10 1.5/10 7.0/10 5.5M $65,701
3 Technicians and associate professionals 5.5/10 3.5/10 4.5/10 4.8M $44,450
5 Service and sales workers 3.5/10 4.5/10 1.5/10 5.1M $24,976
6 Skilled agricultural, forestry and fishery workers 3.0/10 6.5/10 1.0/10 354K N/A
8 Plant and machine operators and assemblers 3.0/10 7.5/10 1.0/10 1.5M $40,424
0 Armed forces occupations 2.5/10 3.0/10 1.0/10 30K N/A
7 Craft and related trades workers 2.5/10 4.5/10 1.0/10 2.1M $43,486
9 Elementary occupations 2.0/10 5.5/10 0.5/10 3.1M $24,240

AI/robotics/WFH scores are research-based estimates (Frey-Osborne, OECD, IMF 2024), not official statistics. Hover occupation name for rationale. Employment from: ILO ILOSTAT (CC BY 4.0), ONS ASHE Table 14 (Open Government Licence v3.0).

AI Disruption Context

World Bank indicators showing when disruption will arrive and how resilient the workforce is.

Risk Velocity
10.0/10
Disruption imminent (1-3 years)
Recovery Resilience
7.3/10
High resilience - workers can pivot
Sovereign Buffer
1.3/10
Weak buffer - mass displacement = crisis
Demographic Alignment
Labor shortage solver
Aging workforce means automation fills critical gaps

Source: World Bank Open Data (CC BY 4.0) - IT.NET.BBND.P2, IT.NET.SECR.P6, HD_HCIP_OTJL_TO, SP social protection indicators.

Frequently Asked Questions

Which job is most at risk from AI in United Kingdom?
Clerical support workers has the highest AI exposure score in United Kingdom at 8.5/10. This occupation involves routine information handling that current AI systems can perform effectively.
What is the average AI exposure score in United Kingdom?
The workforce-weighted average AI exposure score in United Kingdom is 5.1/10, covering 34.1M workers across 10 occupation groups. Each group is weighted by its share of total employment.
Which jobs are safest from AI in United Kingdom?
Elementary occupations has the lowest AI exposure score in United Kingdom at 2.0/10. These roles require physical presence or manual dexterity in unpredictable environments that current AI cannot automate at scale.
When will AI disruption arrive in United Kingdom?
Based on digital infrastructure readiness, United Kingdom scores 10.0/10 for AI Risk Velocity. Disruption imminent (1-3 years). This is derived from World Bank broadband and secure internet server data.
How well can United Kingdom's workforce adapt to AI disruption?
United Kingdom scores 7.3/10 for Workforce Recovery Capacity. High resilience - workers can pivot. This combines the World Bank Human Capital Index on-the-job learning score and social protection coverage data.
Which occupation pays the most in United Kingdom?
The highest-paid occupation in United Kingdom is Managers at $65,701 per year. The lowest-paid is Elementary occupations at $24,240 per year.
Is automation good or bad for United Kingdom's workforce?
United Kingdom is classified as 'Labor shortage solver'. Aging workforce means automation fills critical gaps. This is based on World Bank old-age dependency ratio and fertility rate data.
Where does the United Kingdom workforce data come from?
The United Kingdom data comes from: ILO ILOSTAT (CC BY 4.0); ONS ASHE Table 14 (Open Government Licence v3.0); OECD Average Annual Wages (USD PPP, 2024). All data is from official government or intergovernmental sources and is freely available at worldjobsdata.com.
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