Receptionist (general)
AI displacement risk
47%
Range 40.02–53.84%
Receptionist (general) has 70% AI task overlap with only 17% human bottleneck protection — higher risk than 92% of occupations in the live market. Structural displacement pressure is significant.
Clerical Support Workers·SGD 2,724/mo (1,977–3,349)·~3.1K 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
70% of tasks overlap with current AI
17% human advantage from judgment & presence
36% demand buffer from the local labour market
AI usage 27pp above 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 70% AI task overlap (based on Felten AIOE, Anthropic Economic Index, Eloundou GPT exposure, and ILO occupational exposure), the Receptionist (general) tasks most exposed include: reservation management, menu recommendations, order processing, loyalty program tracking, and basic customer query handling via chatbots.
- • Operate telephone switchboard to answer, screen, or forward calls, providing information, taking messages, or scheduling appointments.
- • Schedule appointments and maintain and update appointment calendars.
- • Hear and resolve complaints from customers or the public.
O*NET tasks for this occupation with the most observed AI usage (Anthropic task data).
What AI can't do here
At 17% human bottleneck protection, the tasks that remain hardest to automate for Receptionist (general) include: genuine hospitality and warmth, reading customer moods, handling complaints gracefully, creating memorable experiences, and adapting service to cultural expectations.
Main insulation channels: Relational work + High-stakes decisions — the work-context dimensions behind this occupation's human bottleneck.
Skills to focus on
Brynjolfsson et al. (2023) found customer service agents using AI saw +14% productivity, with the biggest gains among junior workers — AI compressed the experience gap.
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
Receptionist (general) 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
Risk-reducingHigh displacement pressure, but comparatively credible risk-reducing moves exist — the strongest scores 67% match. Escape-route quality, not pressure alone, shapes how risk resolves.
Compare within Clerical Support Workers
See how this compares to similar occupations
Compare with... →Classification
Higher risk than 92% of occupations · V7 structural score
Raw scores
AIOE 0.542 · θ 0.629 · C-AIOE 0.464
Stability
watch · Optimistic 43% · Pessimistic 56%
Score range (best/worst case)
Exposure 61–77% · Net risk 40.02–53.84%
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.-2.1pp versus retained V6 baseline.
Wage range (SGD/mo)
25th 1,977 · Median 2,724 · 75th 3,349
Evidence & sources
Data matching
direct · SSOC 42241
Real-world AI usage: +27% vs estimated
Data quality
60% · Matching 0.36 · Market data 0.70 · Freshness 0.84
100% weighted task match · 32% 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.
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.
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%.
Gross wage by sex
Female median 18% higherPublished June 2024 gross wage medians: male $2,334, female $2,752.
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
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 Receptionist (general)?
Receptionist (general) has 70% AI task overlap with only 17% human bottleneck protection — higher risk than 92% of occupations in the live market. Structural displacement pressure is significant. Net displacement risk: 47% (High). Median wage: SGD 2,724/month.
What is the AI risk score for Receptionist (general)?
Receptionist (general) has an AI displacement risk of 47%, rated High. AI task overlap: 70%. Human advantage: 17%. Local demand buffer: 36%.
What career transitions are available for Receptionist (general)?
Receptionist (general) has modeled transition pathways to related occupations. The strongest adjacent pathway is Undertaker, based on skill and wage similarity (model-estimated). Transition scoring accounts for wage preservation, training ease, and destination quality.
How does Receptionist (general) salary compare in the live market?
Receptionist (general) earns a median gross wage of SGD 2,724/month in the live market (25th-75th percentile: SGD 1,977-3,349). This is 39% below median across all 562 scored occupations, and 15% below group median within Clerical Support Workers occupations.