Postal service counter clerk
AI Exposure Rank
67/100
Range 53–81/100 across source-weight sensitivity checks
Postal service counter clerk has an AI Exposure Rank of 67/100, meaning its work is more exposed to current AI capabilities than approximately 67% of Singapore occupations. The evidence currently points to workflow redesign; this is a relative rank, not a probability of job loss.
Clerical Support Workers·SGD 2,392/mo (2,073–3,012)·~2.9K 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
67% of tasks overlap with current AI
19% human advantage from judgment & presence
30% demand buffer from the local labour market
AI usage 13pp below 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 67% AI task overlap (based on Felten AIOE, Anthropic Economic Index, Eloundou GPT exposure, and ILO occupational exposure), the Postal service counter clerk tasks most exposed include: data entry, invoice processing, appointment scheduling, document filing, and standard correspondence drafting.
- • Weigh letters and parcels, compute mailing costs based on type, weight, and destination, and affix correct postage.
- • Check mail to ensure correct postage and that packages and letters are in proper condition for mailing.
- • Sort incoming and outgoing mail, according to type and destination, by hand or by operating electronic mail-sorting and scanning devices.
O*NET tasks for this occupation with the most observed AI usage (Anthropic task data).
What AI can't do here
At 19% human bottleneck protection, the tasks that remain hardest to automate for Postal service counter clerk include: exception handling for non-standard requests, institutional knowledge of internal processes, coordinating across departments, and managing sensitive information.
Main insulation channels: High-stakes decisions + 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 are softer, yet retrenchment remains low and hiring still exceeds resignations.
Vacancy
3.1%
↓ 11.4% YoY
Hiring
2.6%
vs 1.6% resign
Retrenchment
1.5
per 1,000 · low
Re-entry
78.5%
find work in 12mo· -1.6pp
Clerical, Sales & Service Workers · 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
Postal service counter clerk 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
Exposure-reducingHigher AI exposure, but comparatively credible exposure-reducing moves exist — the strongest scores 67% match. Escape-route quality and labour demand matter alongside exposure.
Compare within Clerical Support Workers
See how this compares to similar occupations
Compare with... →Classification
More exposed than approximately 66% of occupations · V8 AI Exposure Rank· GCE O-Level / Secondary
Raw scores
AIOE 0.473 · θ 0.635 · C-AIOE 0.402
Stability
watch · Optimistic 41% · Pessimistic 53%
Score range (best/worst case)
Exposure sensitivity 52–81% · Rank sensitivity 53–81/100 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 2,073 · Median 2,392 · 75th 3,012
Evidence & sources
Data matching
direct · SSOC 42112
Real-world AI usage: -13% 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
Common tools (O*NET proxy)
What helps
- Nearby moves and published transition support look reasonably strong.
What could slow it down
- Current demand support is thin, so offsets may take longer to show up.
Worker profile & local context
- Vacancy rate is 3.1% and fell by 0.2 points from last quarter.
- Hiring read: recruitment is running above resignation (2.6% vs 1.6%).
- Retrenchment was low at 1.5 per 1,000 employees.
- 78.5% of retrenched workers re-entered employment within 12 months.
- Employer pressure is moderate, based on 3 recent Singapore-relevant company signals.
Worker profile
Gender mix
24% male / 76% femalePublished Singapore worker composition for the detailed occupation family 42 Customer Services Officers & Clerks.
Employment structure
Employee-heavy99% employees, 1% employers or self-employed workers.
Work arrangement
Mostly full-time13% part-time and 87% full-time in 2025.
Age profile
Older-skewing16% aged 15 to 29, 35% aged 30 to 49, and 49% aged 50 or older.
Qualification mix
Mixed qualificationsSecondary 29%; Diploma / professional qualification 28%.
Where this work is concentrated
Top planning areas
Jurong West, Tampines, Woodlands22% of workers in this occupation group live in these three planning areas.
Residential concentration
Moderately clustered35% live across the top five planning areas in the 2020 Census.
Commute pattern
Longer commutesEstimated average commute 39.7 minutes. 38% 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 Postal service counter clerk?
Postal service counter clerk has an AI Exposure Rank of 67/100, meaning its work is more exposed to current AI capabilities than approximately 67% of Singapore occupations. The evidence currently points to workflow redesign; this is a relative rank, not a probability of job loss. AI Exposure Rank: 67/100 (High). Median wage: SGD 2,392/month.
What is the AI exposure rank for Postal service counter clerk?
Postal service counter clerk has an AI Exposure Rank of 67/100, rated High. It ranks higher than approximately 67% of Singapore occupations for exposure to current AI capabilities; it is not a job-loss probability.
What career transitions are available for Postal service counter clerk?
Postal service counter clerk has modeled transition pathways to related occupations. The strongest adjacent pathway is Money changer, based on skill and wage similarity (model-estimated). Transition scoring accounts for wage preservation, training ease, and destination quality.
How does Postal service counter clerk salary compare in the live market?
Postal service counter clerk earns a median gross wage of SGD 2,392/month in the live market (25th-75th percentile: SGD 2,073-3,012). This is 47% below median across all 562 scored occupations, and 25% below group median within Clerical Support Workers occupations.