Electrical household appliance repairer
AI Exposure Rank
17/100
Range 12–21/100 across source-weight sensitivity checks
Electrical household appliance repairer has an AI Exposure Rank of 17/100, meaning its work is more exposed to current AI capabilities than approximately 17% of Singapore occupations. The evidence currently points to limited direct change; this is a relative rank, not a probability of job loss.
Craftsmen & Related Trades Workers·SGD 2,797/mo (1,900–3,323)·~1.1K workers in SG·Updated 2026-06-11
Relative AI exposure, not a prediction of job loss. Hiring, wages and role design depend on many forces this rank does not forecast.
Why This Score
21% of tasks overlap with current AI
65% human advantage from judgment & presence
28% demand buffer from the local labour market
AI usage 31pp above theoretical exposure
These factors interact with each other — the final score is not a simple sum of these bars.
The evidence behind this occupation's AI exposure, with human-work and demand context shown separately. Score stability: watch. How this works
Tasks AI can handle
With 21% AI task overlap (based on Felten AIOE, Anthropic Economic Index, Eloundou GPT exposure, and ILO occupational exposure), the Electrical household appliance repairer tasks most exposed include: predictive maintenance scheduling, safety checklist automation, inventory management, and remote monitoring via sensors.
- • Bill customers for repair work, and collect payment.
- • Observe and examine appliances during operation to detect specific malfunctions such as loose parts or leaking fluid.
- • Talk to customers or refer to work orders to establish the nature of appliance malfunctions.
O*NET tasks for this occupation with the most observed AI usage (Anthropic task data).
What AI can't do here
At 65% human bottleneck protection, the tasks that remain hardest to automate for Electrical household appliance repairer include: physical dexterity on job sites, real-time environmental adaptation, operating heavy equipment safely, and handling unexpected on-site conditions.
Main insulation channels: Non-routine work + High-stakes decisions — the work-context dimensions behind this occupation's human bottleneck.
Skills to focus on
Sources: Felten AIOE (2021), Anthropic Economic Index (2026), Eloundou GPT Exposure (Science, 2024), ILO GenAI (2025), Pizzinelli et al. bottleneck model. Full methodology.
Singapore Now
Current labour market conditions and how they affect this role.
Still healthy locally. Hiring remains positive and retrenchment stays low, even if demand is not accelerating.
Vacancy
2.8%
↑ 16.7% YoY
Hiring
2.4%
vs 1.5% resign
Retrenchment
1.5
per 1,000 · low
Re-entry
78.1%
find work in 12mo· -4.5pp
Production & Transport Operators, Cleaners & Labourers · 2025 Q4
Top Industries
Industry vacancy overlays use the latest published detailed cross-tab, which can lag the main labour monitor.
What You Can Do
Electrical household appliance repairer has some offset potential, but it depends on transition pathways holding up in practice and on workers clearing the main switching frictions.
Published transition support
Related roles you could transition to
Similarity-basedCompare within Craftsmen & Related Trades Workers
See how this compares to similar occupations
Compare with... →Classification
More exposed than approximately 17% of occupations · V8 AI Exposure Rank· Polytechnic / ITE Diploma
Raw scores
AIOE -0.853 · θ 0.694 · C-AIOE -0.675
Stability
watch · Optimistic 3% · Pessimistic 10%
Score range (best/worst case)
Exposure sensitivity 13–30% · Rank sensitivity 12–21/100 across source-weight sensitivity checks
Scoring basis
V8 AI Exposure Rank. A relative Singapore occupation index. It ranks AI task exposure; it is not a probability of job loss or a percentage of tasks.
Wage range (SGD/mo)
25th 1,900 · Median 2,797 · 75th 3,323
Evidence & sources
Data matching
direct · SSOC 74123
Real-world AI usage: +31% vs estimated
Data quality
medium evidence · 4 exposure sources · direct mapping
Capped at high · Final rating: medium · capped for conflicting signals
100% weighted task match · 0% effective coverage
AI overlap by data source
Weights: aioe 24% · anthropic 26% · eloundou 25% · ilo 26%
Conflicting data signals
Tools & offset factors
What helps
- Nearby moves and published transition support look reasonably strong.
Worker profile & local context
- Vacancy rate is 2.8% and rose by 0.8 points from last quarter.
- Hiring read: recruitment is running above resignation (2.4% vs 1.5%).
- Retrenchment was low at 1.5 per 1,000 employees.
- 78.1% of retrenched workers re-entered employment within 12 months.
- Employer pressure is low, based on 1 recent Singapore-relevant company signals.
Worker profile
Gender mix
96% male / 4% femalePublished Singapore worker composition for the detailed occupation family 74 Electrical & Electronic Trades Workers.
Employment structure
Employee-heavy85% employees, 15% employers or self-employed workers.
Work arrangement
Mostly full-time13% part-time and 87% full-time in 2025.
Age profile
Older-skewing7% aged 15 to 29, 25% aged 30 to 49, and 67% aged 50 or older.
Qualification mix
Non-degree heavyBelow secondary 38%; Secondary 27%.
Where this work is concentrated
Top planning areas
Woodlands, Jurong West, Yishun25% of workers in this occupation group live in these three planning areas.
Residential concentration
More concentrated39% live across the top five planning areas in the 2020 Census.
Commute pattern
Mid-range commutesEstimated average commute 35.1 minutes. 28% take 46 minutes or more.
Role profile
How this role's work breaks down across key dimensions. This is a general profile, not an individual measurement.
Workflow dimensions (0 = low, 1 = high)
How this changes by career stage
Career stage can change the task mix and human context. These directional profiles are illustrative, not occupation-level forecasts of hiring or displacement.
Frequently asked questions
Will AI replace Electrical household appliance repairer?
Electrical household appliance repairer has an AI Exposure Rank of 17/100, meaning its work is more exposed to current AI capabilities than approximately 17% of Singapore occupations. The evidence currently points to limited direct change; this is a relative rank, not a probability of job loss. AI Exposure Rank: 17/100 (Very Low). Median wage: SGD 2,797/month.
What is the AI exposure rank for Electrical household appliance repairer?
Electrical household appliance repairer has an AI Exposure Rank of 17/100, rated Very Low. It ranks higher than approximately 17% of Singapore occupations for exposure to current AI capabilities; it is not a job-loss probability.
What career transitions are available for Electrical household appliance repairer?
Electrical household appliance repairer has modeled transition pathways to related occupations. The strongest adjacent pathway is Electrical lift, escalator and related equipment fitter, based on skill and wage similarity (model-estimated). Transition scoring accounts for wage preservation, training ease, and destination quality.
How does Electrical household appliance repairer salary compare in the live market?
Electrical household appliance repairer earns a median gross wage of SGD 2,797/month in the live market (25th-75th percentile: SGD 1,900-3,323). This is 38% below median across all 562 scored occupations, and 14% below group median within Craftsmen & Related Trades Workers occupations.