Concierge (hotel)
AI Exposure Rank
68/100
Range 62–70/100 across source-weight sensitivity checks
Concierge (hotel) has an AI Exposure Rank of 68/100, meaning its work is more exposed to current AI capabilities than approximately 68% of Singapore occupations. The evidence currently points to workflow redesign; this is a relative rank, not a probability of job loss.
Cleaners, Labourers & Related Workers·SGD 3,002/mo (2,580–3,488)·~1.5K workers in SG·Updated 2026-07-17
Relative AI exposure, not a prediction of job loss. Hiring, wages and role design depend on many forces this rank does not forecast.
How This Rank Is Built
The source percentiles are combined using the displayed reliability weights, then ranked against all 562 Singapore occupations. This is not a percentage of tasks and not a job-loss probability.
Likely job pathway
Workflow redesign
Current demand context
Mixed current demand
Pathway and demand are reported beside the exposure rank. Current demand does not change the rank.
The evidence behind this occupation's AI exposure, with human-work and demand context shown separately. How this works
Tasks AI can handle
With 68% AI task overlap (based on Felten AIOE, Anthropic Economic Index, and Eloundou GPT exposure), the Concierge (hotel) tasks most exposed include: predictive maintenance scheduling, safety checklist automation, inventory management, and remote monitoring via sensors.
- • Make travel arrangements for sightseeing or other tours.
- • Provide information about local features, such as shopping, dining, nightlife, or recreational destinations.
- • Plan special events, parties, or meetings, which may include booking musicians or celebrities.
O*NET tasks for this occupation with the most observed Claude usage (Anthropic task data).
What AI can't do here
At 19% human bottleneck protection, the tasks that remain hardest to automate for Concierge (hotel) include: physical dexterity on job sites, real-time environmental adaptation, operating heavy equipment safely, and handling unexpected on-site conditions.
Main insulation channels: Non-routine work + Relational work — the work-context dimensions behind this occupation's human bottleneck.
- • Book airline or train tickets, reserve rental cars, or arrange shuttle service for guests.
- • Assist guests with special needs by providing equipment such as wheelchairs.
Highest-importance tasks with no observed Claude usage in the same data — absence of observed usage, not proof of immunity.
Skills to focus on
Sources: Felten AIOE (2021), Anthropic Economic Index (2026), Eloundou GPT Exposure (Science, 2024), Pizzinelli et al. bottleneck model. Full methodology.
From exposure to employment
What could change the employment outcome?
AI capability is only the starting point. Adoption, task design, human oversight, demand, mobility and evidence quality determine how exposure may resolve in practice.
Workplace adoption
Occupation-level adoption unknown
MOM does not publish a directly mappable adoption rate for the listed industries.
Task structure
Task evidence available
88% weighted task match · 20% effective coverage
Human advantage
Coordination and judgment still matter
At 19% human bottleneck protection, the tasks that remain hardest to automate for Concierge (hotel) include: physical dexterity on job sites, real-time environmental adaptation, operating heavy equipment safely, and handling unexpected on-site conditions.
Hiring and demand
2.3% vacancy rate · 2026 Q1
Production and transport vacancies fell back from the Q4 spike and were slightly below a year earlier. Hiring remained net positive, retrenchments declined, and six-month re-entry improved. In 2025, this broad occupation group had 4.9% time-related underemployment and 19.2% non-permanent employment. Across the published male and female series, CPI-adjusted median income changed +0.2% to +8.6% from 2018 to 2023.
Career transitions
Sports and recreational attendant (e.g. golf marshal, golf caddie, fun fair attendant, bowling alley attendant, swimming
easy modeled transition; outcomes still depend on skills, wages and openings.
Evidence strength
medium confidence
3 exposure sources · sensitivity 62–70/100 across source-weight sensitivity checks.
These lenses are reported separately and do not alter AI Exposure Rank. Labour-market figures describe a broad official occupation cluster, not this SSOC occupation alone.
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
2.3%
↓ 4.2% YoY
Hiring
1.7%
vs 1.2% resign
Retrenchment
0.3
per 1,000 · low
Re-entry
76.9%
find work in 12mo· -1.2pp
Production & Transport Operators, Cleaners & Labourers · 2026 Q1
Top Industries
Industry vacancy overlays use the latest published detailed cross-tab, which can lag the main labour monitor.
What You Can Do
Concierge (hotel) 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 82% match. Escape-route quality and labour demand matter alongside exposure.
Compare within Cleaners, Labourers & Related Workers
See how this compares to similar occupations
Compare with... →Classification
More exposed than approximately 67% of occupations · V8 AI Exposure Rank· GCE O-Level / Secondary
Raw scores
AIOE 0.856 · θ 0.634 · C-AIOE 0.728
Stability
stable · Optimistic 31% · Pessimistic 42%
Score range (best/worst case)
Exposure sensitivity 62–71% · Rank sensitivity 62–70/100 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 2,580 · Median 3,002 · 75th 3,488
Evidence & sources
Data matching
direct · SSOC 96272
Real-world AI usage: +15% vs estimated
Data quality
medium evidence · 3 exposure sources · direct mapping
88% weighted task match · 20% effective coverage
AI overlap by data source
Weights: aioe 32% · anthropic 35% · eloundou 33%
Conflicting data signals
Worker profile & local context
- Vacancy rate is 2.3% and fell by 0.5 points from last quarter.
- Hiring read: recruitment is running above resignation (1.7% vs 1.2%).
- Retrenchment was low at 0.3 per 1,000 employees.
- 76.9% of retrenched workers re-entered employment within 12 months.
- Employer pressure is low, based on 1 captured Singapore-relevant company signals through 2025-10-06.
Worker profile
Gender mix
47% male / 53% femalePublished Singapore worker composition for the detailed occupation family 96 Waste Collection, Recycling & Material Recovery Workers & Other Elementary Workers.
Employment structure
Employee-heavy96% employees, 4% employers or self-employed workers.
Work arrangement
Part-time meaningful33% part-time and 67% full-time in 2025.
Age profile
Older-skewing5% aged 15 to 29, 14% aged 30 to 49, and 81% aged 50 or older.
Qualification mix
Non-degree heavyBelow secondary 56%; Secondary 18%.
Gross wage by sex
Female median 8% higherPublished June 2024 gross wage medians: male $2,886, female $3,120.
Where this work is concentrated
Top planning areas
Jurong West, Woodlands, Bedok22% 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
Mid-range commutesEstimated average commute 32.8 minutes. 27% 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.
General role profile on a 0–100 scale. These are modelling inputs, not measurements of an individual job or worker.
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 Concierge (hotel)?
Concierge (hotel) has an AI Exposure Rank of 68/100, meaning its work is more exposed to current AI capabilities than approximately 68% of Singapore occupations. The evidence currently points to workflow redesign; this is a relative rank, not a probability of job loss. AI Exposure Rank: 68/100 (High). Median wage: SGD 3,002/month.
What is the AI exposure rank for Concierge (hotel)?
Concierge (hotel) has an AI Exposure Rank of 68/100, rated High. It ranks higher than approximately 68% of Singapore occupations for exposure to current AI capabilities; it is not a job-loss probability.
What career transitions are available for Concierge (hotel)?
Concierge (hotel) has modeled transition pathways to related occupations. The strongest adjacent pathway is Car park attendant, based on skill and wage similarity (model-estimated). Transition scoring accounts for wage preservation, training ease, and destination quality.
How does Concierge (hotel) salary compare in the live market?
Concierge (hotel) earns a median gross wage of SGD 3,002/month in the live market (25th-75th percentile: SGD 2,580-3,488). This is 33% below median across all 562 scored occupations, and 55% above group median within Cleaners, Labourers & Related Workers occupations.