Cleaning supervisor
AI Exposure Rank
35/100
Range 21–44/100 across source-weight sensitivity checks
Cleaning supervisor has an AI Exposure Rank of 35/100, meaning its work is more exposed to current AI capabilities than approximately 35% of Singapore occupations. The evidence currently points to limited direct change; this is a relative rank, not a probability of job loss.
Cleaners, Labourers & Related Workers·SGD 2,210/mo (1,600–2,976)·~7.5K 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
Limited direct change
Current demand context
Strong 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. Score stability: watch. How this works
Tasks AI can handle
With 35% AI task overlap (based on Felten AIOE, Anthropic Economic Index, and Eloundou GPT exposure), the Cleaning supervisor tasks most exposed include: predictive maintenance scheduling, safety checklist automation, inventory management, and remote monitoring via sensors.
What AI can't do here
At 78% human bottleneck protection, the tasks that remain hardest to automate for Cleaning supervisor 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 + 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), 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 limited
Task-weighted shadow evidence is not active for this occupation yet.
Human advantage
Coordination and judgment still matter
At 78% human bottleneck protection, the tasks that remain hardest to automate for Cleaning supervisor 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
Office, commercial and industrial establishments multi-skilled cleaner cum machine operator
moderate modeled transition; outcomes still depend on skills, wages and openings.
Evidence strength
medium confidence
3 exposure sources · sensitivity 21–44/100 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
Cleaning supervisor 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-basedCompare within Cleaners, Labourers & Related Workers
See how this compares to similar occupations
Compare with... →Classification
More exposed than approximately 35% of occupations · V8 AI Exposure Rank· Polytechnic / ITE Diploma
Raw scores
AIOE -0.570 · θ 0.722 · C-AIOE -0.435
Stability
watch · Optimistic 3% · Pessimistic 7%
Score range (best/worst case)
Exposure sensitivity 21–48% · Rank sensitivity 21–44/100 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 1,600 · Median 2,210 · 75th 2,976
Evidence & sources
Data matching
direct · SSOC 91000
Real-world AI usage: +40% vs estimated
Data quality
medium evidence · 3 exposure sources · direct mapping
Task-weighted shadow evidence is not active for this occupation yet.
AI overlap by data source
Weights: aioe 32% · anthropic 35% · eloundou 33%
Conflicting data signals
Tools & offset factors
What helps
- A meaningful share of the work can likely be reorganized around AI rather than removed outright.
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
44% male / 57% femalePublished Singapore worker composition for the detailed occupation family 91 Cleaners & Related 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 20% lowerPublished June 2024 gross wage medians: male $2,250, female $1,800.
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 Cleaning supervisor?
Cleaning supervisor has an AI Exposure Rank of 35/100, meaning its work is more exposed to current AI capabilities than approximately 35% of Singapore occupations. The evidence currently points to limited direct change; this is a relative rank, not a probability of job loss. AI Exposure Rank: 35/100 (Low). Median wage: SGD 2,210/month.
What is the AI exposure rank for Cleaning supervisor?
Cleaning supervisor has an AI Exposure Rank of 35/100, rated Low. It ranks higher than approximately 35% of Singapore occupations for exposure to current AI capabilities; it is not a job-loss probability.
What career transitions are available for Cleaning supervisor?
Cleaning supervisor has modeled transition pathways to related occupations. The strongest adjacent pathway is Office, commercial and industrial establishments multi-skilled cleaner cum machine operator, based on skill and wage similarity (model-estimated). Transition scoring accounts for wage preservation, training ease, and destination quality.
How does Cleaning supervisor salary compare in the live market?
Cleaning supervisor earns a median gross wage of SGD 2,210/month in the live market (25th-75th percentile: SGD 1,600-2,976). This is 51% below median across all 562 scored occupations, and 14% above group median within Cleaners, Labourers & Related Workers occupations.