Structural pressure
4%
Very Low RiskAutomotive mechanic
This model suggests AI is unlikely to significantly disrupt Automotive mechanic. low exposure with limited overlap across core tasks.
Limited buffers available against the structural pressure.
Why This Score
11% of tasks overlap with current AI
61% human advantage from judgment & presence
26% demand buffer from SG labour market
AI usage 5pp above theoretical exposure
These factors combine multiplicatively — larger bars do not mean proportionally larger contributions to the final score.
Exposure × (1 − Bottleneck) × Market Modifier. Band stability: watch. How this works
Tasks AI can handle
Predictive maintenance scheduling, safety checklist automation, inventory management, and remote monitoring via sensors.
Where humans stay essential
Physical dexterity on job sites, real-time environmental adaptation, operating heavy equipment safely, and handling unexpected on-site conditions.
Skills to focus on
Role profile
Heuristic workflow context from shared occupation archetypes. This profile helps interpret the score; it is not a direct occupation-level measurement and is not part of the core net-risk formula.
Workflow dimensions (0 = low, 1 = high)
Singapore Now
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 · Q4 2025 full
Top Industries
Industry vacancy overlays use the latest published detailed cross-tab, which can lag the main labour monitor.
How this changes by career stage
What You Can Do
Automotive mechanic 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
Adjacent pathways to investigate
Similarity-basedSee how this compares to similar occupations
Compare with... →Classification
Higher risk than 15% of occupations· Polytechnic / ITE Diploma
Raw scores
AIOE -0.955 · θ 0.688 · C-AIOE -0.725
Stability
watch · Optimistic 1% · Pessimistic 7%
Sensitivity band
Exposure 10–12% · Net risk 3.07–4.98%
Scoring basis
Not published. No scoring-basis metadata is available for this occupation.
Wage range (SGD/mo)
25th 2,160 · Median 2,776 · 75th 3,400
Evidence & sources
Crosswalk
direct · SSOC 72310
Anthropic: +5pp vs theory
Evidence quality
88% · Crosswalk 1.00 · Market 0.70 · Fresh 0.84
100% weighted task match · 0% effective coverage
Exposure by source
Weights: aioe 24% · anthropic 26% · eloundou 25% · ilo 26%
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
92% male / 8% femalePublished Singapore worker composition for the detailed occupation family 72 Metal, Machinery & Related 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.