UK AI Job-Risk Index · SOC 2010 2129
Ranks #62 of 293 for AI exposure (1 = most exposed)
How exposed to AI are engineering professionals n.e.c.?
81/100
AI exposure score (percentile across all 365 occupations DfE scored)
Very high#62
of 293 UK occupations (1 = most exposed)
£43,962
median full-time pay (ONS ASHE 2020) · 178,000 employee jobs
Engineering professionals n.e.c. sits in the very high exposure band: its abilities overlap with current AI applications more than about 81% of the 365 UK occupations the Department for Education scored. High exposure usually means AI can help with many of the tasks involved, such as drafting, analysis or information handling. That can change how the job is done, but it is not a forecast that the job will disappear.
Underlying scores: AIOE (all AI) 1.09, LLM exposure 0.83 (standardised; 0 is the average occupation). Skill level: Level 4. Pay and job counts are 2020 figures, so use them to compare occupations rather than as current salaries.
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Job titles in this occupation
Titles the ONS SOC 2010 coding index places in unit group 2129 (30 of 50 shown). If your job title is here, this page uses the right figures for you.
assayer · assayist · ceramist · ceramicist · head brewer · tribologist · metallurgist · patent agent · technologist · under brewer · fuel engineer · food scientist · glass engineer · metallographer · patent analyst · technical dyer · vinegar brewer · working brewer · assay assistant · patent engineer · sensory manager · textile adviser · nuclear engineer · patent associate · project engineer · technical brewer · traffic engineer · ceramics engineer · dyeing technician · energy consultant
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Lower-risk related jobs
Occupations in the same SOC 2010 sub-major group with a lower AI exposure score, highest-paid first. Pay difference is against £43,962 (ONS ASHE 2020 median, full-time). Switching usually needs retraining; this is a starting point, not advice.
| Occupation | Exposure | Median pay | Difference |
|---|---|---|---|
| Electrical engineers | 68/100 | £52,064 | +£8,102 |
| IT specialist managers | 78/100 | £50,749 | +£6,787 |
| Research and development managers | 75/100 | £49,000 | +£5,038 |
| Mechanical engineers | 74/100 | £42,745 | −£1,217 |
| Physical scientists | 81/100 | £41,511 | −£2,451 |
Occupations with similar exposure
- Business and related research professionals (82/100)
- Financial institution managers and directors (81/100)
- Business sales executives (81/100)
- Physical scientists (81/100)
← #61 Business and related research professionals · #63 Financial institution managers and directors →
FAQ: Engineering professionals n.e.c. and AI
Will AI replace engineering professionals n.e.c.?
The index does not predict job losses. Engineering professionals n.e.c. has an AI exposure score of 81/100 (very high band), ranking #62 of 293 UK occupations, where 1 is the most exposed. High exposure means AI can help with many of the tasks involved, which usually changes how the job is done.
How does this compare with similar jobs?
Engineering professionals n.e.c. is one of 20 occupations in its SOC 2010 sub-major group in the index; 8 of the others are more exposed to AI.
How much do engineering professionals n.e.c. earn?
Median gross annual pay for full-time employees was £43,962 in ONS ASHE 2020 (Table 14), across about 178,000 employee jobs. These are 2020 figures, so use them to compare jobs rather than as current salaries.
Which related jobs are less exposed to AI?
In the same sub-major group, lower-exposure occupations include Electrical engineers (68/100, £52,064), IT specialist managers (78/100, £50,749), Research and development managers (75/100, £49,000).
Where does this data come from?
AI exposure uses Department for Education (2023) AI Occupational Exposure (AIOE) scores; pay and job counts come from ONS ASHE 2020. Job titles come from the ONS SOC 2010 coding index.
Source: Department for Education (2023), The impact of AI on UK jobs and training (AIOE scores); ONS ASHE 2020 Table 14; job titles from the ONS SOC 2010 coding index (v7). Exposure is not a prediction of job loss. Methodology · Embed this data
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