Quality control/assurance engineer
AI Exposure Rank
58/100
Range 52–70/100 across source-weight sensitivity checks
Quality control/assurance engineer has an AI Exposure Rank of 58/100, meaning its work is more exposed to current AI capabilities than approximately 58% of Singapore occupations. The evidence currently points to workflow redesign; this is a relative rank, not a probability of job loss.
Professionals·SGD 6,310/mo (4,794–8,471)·~2.4K 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
58% of tasks overlap with current AI
71% human advantage from judgment & presence
47% demand buffer from the local labour market
AI usage 56pp below theoretical exposure
On the Shortage Occupation List list — government recognises hiring need
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. How this works
Tasks AI can handle
With 58% AI task overlap (based on Felten AIOE, Anthropic Economic Index, Eloundou GPT exposure, and ILO occupational exposure), the Quality control/assurance engineer tasks most exposed include: financial modeling, data extraction from filings, ratio analysis, report generation, transaction categorization, and regulatory document summarization.
- • Compile laboratory test data and perform appropriate analyses.
- • Document methods used and write technical reports containing information collected.
- • Develop specialized computer software routines to customize and integrate image analysis.
O*NET tasks for this occupation with the most observed AI usage (Anthropic task data).
What AI can't do here
At 71% human bottleneck protection, the tasks that remain hardest to automate for Quality control/assurance engineer include: judgment on risk vs. return, client advisory relationships, regulatory interpretation in edge cases, fraud detection in novel scenarios, and strategic capital allocation.
Main insulation channels: Deep preparation + Non-routine 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), ILO GenAI (2025), Pizzinelli et al. bottleneck model. Full methodology.
Singapore Now
Current labour market conditions and how they affect this role.
Cooling, but not collapsing. Vacancies and re-entry are softer, yet retrenchment remains low and hiring still exceeds resignations.
Vacancy
3.1%
↓ 3.1% YoY
Hiring
1.5%
vs 0.9% resign
Retrenchment
1.5
per 1,000 · low
Re-entry
67.7%
find work in 12mo· -5.3pp
Professionals, Managers, Executives & Technicians · 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
Quality control/assurance engineer has some offset potential, but it depends on task redesign holding up in practice and on workers clearing the main switching frictions.Adjacent routes exist, but switching friction is still high.
Published transition support
Related roles you could transition to
Exposure-reducingThis occupation has higher relative AI exposure, and its best adjacent move ranks in the weakest quarter of exposure-reducing options. Mobility outcomes also depend on demand, wages, skills and access to credible transitions. See all occupations in this quadrant.
Compare within Professionals
See how this compares to similar occupations
Compare with... →Classification
More exposed than approximately 57% of occupations · V8 AI Exposure Rank· University Degree
Raw scores
AIOE 1.283 · θ 0.706 · C-AIOE 0.999
Stability
stable · Optimistic 9% · Pessimistic 15%
Score range (best/worst case)
Exposure sensitivity 45–72% · Rank sensitivity 52–70/100 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 4,794 · Median 6,310 · 75th 8,471
Evidence & sources
Data matching
direct · SSOC 21414
SOL 2026: prefix match
Real-world AI usage: -56% vs estimated
Data quality
medium evidence · 4 exposure sources · direct mapping
100% weighted task match · 6% effective coverage
AI overlap by data source
Weights: aioe 24% · anthropic 26% · eloundou 25% · ilo 26%
Conflicting data signals
Tools & offset factors
What helps
- A meaningful share of the work can likely be reorganized around AI rather than removed outright.
What could slow it down
- Credential or licensing barriers could make switching harder than the adjacent-role list suggests.
Worker profile & local context
- Vacancy rate is 3.1% and was essentially flat versus last quarter.
- Hiring read: recruitment is running above resignation (1.5% vs 0.9%).
- Retrenchment was low at 1.5 per 1,000 employees.
- 67.7% of retrenched workers re-entered employment within 12 months.
- Live job ads show 0 visible postings in the last 30 days, led by regulatory standards, Supplier Quality Engineering, Engineering Education.
- Employer pressure is low, based on 2 recent Singapore-relevant company signals.
Worker profile
Gender mix
69% male / 31% femalePublished Singapore worker composition for the detailed occupation family 21 Science & Engineering Professionals.
Employment structure
Employee-heavy96% employees, 4% employers or self-employed workers.
Work arrangement
Mostly full-time4% part-time and 96% full-time in 2025.
Age profile
Mid-career heavy14% aged 15 to 29, 62% aged 30 to 49, and 24% aged 50 or older.
Qualification mix
Degree-heavyDegree 81%; Diploma / professional qualification 15%.
Gross wage by sex
Near parityPublished June 2024 gross wage medians: male $6,325, female $6,280.
Where this work is concentrated
Top planning areas
Sengkang, Bedok, Tampines19% of workers in this occupation group live in these three planning areas.
Residential concentration
Broadly distributed30% live across the top five planning areas in the 2020 Census.
Commute pattern
Mid-range commutesEstimated average commute 37.5 minutes. 33% 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 Quality control/assurance engineer?
Quality control/assurance engineer has an AI Exposure Rank of 58/100, meaning its work is more exposed to current AI capabilities than approximately 58% of Singapore occupations. The evidence currently points to workflow redesign; this is a relative rank, not a probability of job loss. AI Exposure Rank: 58/100 (Moderate). Median wage: SGD 6,310/month.
What is the AI exposure rank for Quality control/assurance engineer?
Quality control/assurance engineer has an AI Exposure Rank of 58/100, rated Moderate. It ranks higher than approximately 58% of Singapore occupations for exposure to current AI capabilities; it is not a job-loss probability.
What career transitions are available for Quality control/assurance engineer?
Quality control/assurance engineer has modeled transition pathways to related occupations. The strongest adjacent pathway is Financial product structurer, based on skill and wage similarity (model-estimated). Transition scoring accounts for wage preservation, training ease, and destination quality.
How does Quality control/assurance engineer salary compare in the live market?
Quality control/assurance engineer earns a median gross wage of SGD 6,310/month in the live market (25th-75th percentile: SGD 4,794-8,471). This is 40% above median across all 562 scored occupations, and 3% below group median within Professionals occupations.