Supervisor/General foreman (metal, machinery and related trades)
AI displacement risk
3%
Range 0.66–5.27%
Supervisor/General foreman (metal, machinery and related trades) has 31% AI task overlap and 88% human bottleneck protection — lower risk than 87% of occupations in the live market. Current AI capabilities have limited overlap with core tasks.
Craftsmen & Related Trades Workers·SGD 7,712/mo (4,048–9,090)·~1.8K workers in SG·Updated 2026-06-11
Structural pressure, not a prediction of job loss. Displacement tends to arrive through slower hiring, wage compression and role redesign before layoffs.
Why This Score
31% of tasks overlap with current AI
88% human advantage from judgment & presence
41% demand buffer from the local labour market
AI usage 19pp below theoretical exposure
These factors interact with each other — the final score is not a simple sum of these bars.
How much AI overlaps with this job's tasks, offset by human advantages and local demand. Score stability: watch. How this works
Tasks AI can handle
With 31% AI task overlap (based on Felten AIOE, Anthropic Economic Index, and Eloundou GPT exposure), the Supervisor/General foreman (metal, machinery and related trades) tasks most exposed include: predictive maintenance scheduling, safety checklist automation, inventory management, and remote monitoring via sensors.
- • Read work orders or blueprints to determine specified tolerances and sequences of operations for machine setup.
- • Position and move metal wires or workpieces through a series of dies that compress and shape stock to form die impressions.
- • Measure and inspect machined parts to ensure conformance to product specifications.
O*NET tasks for this occupation with the most observed AI usage (Anthropic task data).
What AI can't do here
At 88% human bottleneck protection, the tasks that remain hardest to automate for Supervisor/General foreman (metal, machinery and related trades) include: physical dexterity on job sites, real-time environmental adaptation, operating heavy equipment safely, and handling unexpected on-site conditions.
Main insulation channels: Accountability for others + Relational work — 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), 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
Supervisor/General foreman (metal, machinery and related trades) has some offset potential, but it depends on task redesign holding up in practice and on workers clearing the main switching frictions.
Published transition support
Related roles you could transition to
Similarity-basedSupervisor/General foreman of assemblers and quality checkers →
Crane/Hoist operator (excluding port) →
Building caretaker/Watchman →
See 5 more
Excavating/Trench digging machine operator →
Car park attendant →
Stationary plant and machine supervisor/general foreman →
Sports and recreational attendant (e.g. golf marshal, golf caddie, fun fair attendant, bowling alley attendant, swimming →
Metal heat treating plant operator →
Compare within Craftsmen & Related Trades Workers
See how this compares to similar occupations
Compare with... →Classification
Higher risk than 13% of occupations · V7 structural score
Raw scores
AIOE -0.085 · θ 0.751 · C-AIOE -0.062
Stability
watch · Optimistic 1% · Pessimistic 5%
Score range (best/worst case)
Exposure 20–43% · Net risk 0.66–5.27%
Scoring basis
V7 structural score. Uses task-concentration-weighted exposure, human bottleneck, and demand resilience. V6 baseline fields are retained for release-to-release comparison.-0.2pp versus retained V6 baseline.
Wage range (SGD/mo)
25th 4,048 · Median 7,712 · 75th 9,090
Evidence & sources
Data matching
direct · SSOC 72000
Real-world AI usage: -19% vs estimated
Data quality
76% · Matching 1.00 · Market data 0.70 · Freshness 0.80
100% weighted task match · 0% effective coverage
AI overlap by data source
Weights: aioe 32% · anthropic 35% · eloundou 33%
Conflicting data signals
Tools & offset factors
What helps
- Nearby moves and published transition support look reasonably strong.
- A meaningful share of the work can likely be reorganized around AI rather than removed outright.
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.
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
Senior workers benefit from institutional knowledge and judgment that AI cannot replicate. Entry-level roles have higher task overlap with AI.
Frequently asked questions
Will AI replace Supervisor/General foreman (metal, machinery and related trades)?
Supervisor/General foreman (metal, machinery and related trades) has 31% AI task overlap and 88% human bottleneck protection — lower risk than 87% of occupations in the live market. Current AI capabilities have limited overlap with core tasks. Net displacement risk: 3% (Very Low). Median wage: SGD 7,712/month.
What is the AI risk score for Supervisor/General foreman (metal, machinery and related trades)?
Supervisor/General foreman (metal, machinery and related trades) has an AI displacement risk of 3%, rated Very Low. AI task overlap: 31%. Human advantage: 88%. Local demand buffer: 41%.
What career transitions are available for Supervisor/General foreman (metal, machinery and related trades)?
Supervisor/General foreman (metal, machinery and related trades) has modeled transition pathways to related occupations. The strongest adjacent pathway is Supervisor/General foreman of assemblers and quality checkers, based on skill and wage similarity (model-estimated). Transition scoring accounts for wage preservation, training ease, and destination quality.
How does Supervisor/General foreman (metal, machinery and related trades) salary compare in the live market?
Supervisor/General foreman (metal, machinery and related trades) earns a median gross wage of SGD 7,712/month in the live market (25th-75th percentile: SGD 4,048-9,090). This is 71% above median across all 562 scored occupations, and 138% above group median within Craftsmen & Related Trades Workers occupations.