Total jobs: —
Employment rate: 75.0%
Unemployment: 5.0%
Median FT salary: £39,039
Avg. outlook: — job-weighted
Avg AI exposure: —
Avg salary: —
Occupations: —
Public sector: —
View the Digital AI Exposure scoring prompt (UK adaptation)
You are an expert analyst evaluating how exposed different occupations in the United Kingdom
are to AI and digital automation. You will be given a description of an occupation classified under the ONS
Standard Occupational Classification (SOC) 2020.
Rate the occupation's overall AI Exposure on a scale from 0 to 10.
AI Exposure measures: how much will AI reshape this occupation in the UK context over the next 5-10 years?
Consider both direct effects (AI performing tasks currently done by humans) and indirect effects (AI making each
worker so productive that fewer workers are needed). Account for UK-specific factors: high digital infrastructure
penetration, strong services-led economy (services = ~80% of GDP), London as a global financial/tech hub,
significant public sector employment (NHS, civil service, education), and established regulatory frameworks.
A key signal is whether the job's work product is fundamentally digital. If the occupation involves primarily
working at a computer — writing, coding, analysing data, communicating digitally, processing information — then AI
exposure is inherently high (7+), because AI capabilities in digital domains are advancing rapidly. Conversely,
occupations requiring physical presence, manual dexterity, or real-time human interaction in the physical world
have a natural barrier.
Use these anchors:
0-1: Minimal exposure. Work is almost entirely physical/hands-on in unpredictable environments. Examples:
bricklayer, roofer, refuse collector, agricultural labourer.
2-3: Low exposure. Mostly physical or interpersonal. AI helps at the margins. Examples: electrician, plumber,
nursery nurse, care worker, HGV driver.
4-5: Moderate. A mix of physical and knowledge work. AI meaningfully assists the information-processing parts.
Examples: registered nurse, police officer, secondary teacher, restaurant manager, physiotherapist.
6-7: High exposure. Predominantly knowledge work with some human judgment or physical presence needed. AI tools
already boost productivity significantly. Examples: solicitor, marketing manager, civil servant (HEO+), financial
analyst, HR manager, journalist.
8-9: Very high exposure. Almost entirely computer-based. Core tasks are in domains where AI is rapidly improving.
The occupation faces major restructuring. Examples: software developer, data analyst, graphic designer,
translator, copywriter, bookkeeper, insurance underwriter.
10: Maximum exposure. Routine digital information processing with no physical component. AI can already perform
most tasks. Examples: data entry clerk, telemarketer, basic transcription.
Respond with ONLY a JSON object:
{"exposure": <0-10>, "rationale": "<2-3 sentences with UK-specific context>"}