Pre-school education manager
AI Exposure Rank
30/100
Range 22–38/100 across source-weight sensitivity checks
Pre-school education manager has an AI Exposure Rank of 30/100, meaning its work is more exposed to current AI capabilities than approximately 30% of Singapore occupations. The evidence currently points to limited direct change; this is a relative rank, not a probability of job loss.
Managers·SGD 6,080/mo (2,749–8,434)·~4.3K 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
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. Score stability: watch. How this works
Tasks AI can handle
With 33% AI task overlap (based on Felten AIOE, Anthropic Economic Index, Eloundou GPT exposure, and ILO occupational exposure), the Pre-school education manager tasks most exposed include: generating lesson plans, creating quizzes and practice exercises, summarizing curricula, personalizing reading lists, and grading objective assessments.
- • Prepare, administer, and grade tests and assignments to evaluate students' progress.
- • Observe and evaluate students' performance, behavior, social development, and physical health.
- • Organize and label materials and display students' work.
O*NET tasks for this occupation with the most observed Claude usage (Anthropic task data).
What AI can't do here
At 74% human bottleneck protection, the tasks that remain hardest to automate for Pre-school education manager include: motivating students, adapting to emotional and social dynamics in the classroom, mentoring, handling behavioral issues, and assessing creative or nuanced work.
Main insulation channels: Accountability for others + Non-routine work — the work-context dimensions behind this occupation's human bottleneck.
- • Provide students with disabilities with assistive devices, supportive technology, and assistance accessing facilities, such as restrooms.
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), ILO GenAI (2025), 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
99% weighted task match · 20% effective coverage
Human advantage
Coordination and judgment still matter
At 74% human bottleneck protection, the tasks that remain hardest to automate for Pre-school education manager include: motivating students, adapting to emotional and social dynamics in the classroom, mentoring, handling behavioral issues, and assessing creative or nuanced work.
Hiring and demand
3.4% vacancy rate · 2026 Q1
PMET vacancies increased from Q4 and remained below their year-ago level. Hiring stayed net positive but slowed, while retrenchment incidence remained the highest of the three broad occupation groups. In 2025, this broad occupation group had 0.6% time-related underemployment and 2.7% non-permanent employment. Across the published male and female series, CPI-adjusted median income changed -8.5% to -2.6% from 2018 to 2023.
Career transitions
Aged care services manager
moderate modeled transition; outcomes still depend on skills, wages and openings.
Evidence strength
high confidence
4 exposure sources · sensitivity 22–38/100 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.
Local conditions are under more strain. Vacancies have softened and displacement signals are less forgiving.
Vacancy
3.4%
↓ 2.9% YoY
Hiring
1.2%
vs 0.7% resign
Retrenchment
2.6
per 1,000 · moderate
Re-entry
69.1%
find work in 12mo· +1.4pp
Professionals, Managers, Executives & Technicians · 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
Pre-school education manager 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 Managers
See how this compares to similar occupations
Compare with... →Classification
More exposed than approximately 30% of occupations · V8 AI Exposure Rank· GCE O-Level / Secondary
Raw scores
AIOE -0.121 · θ 0.709 · C-AIOE -0.094
Stability
watch · Optimistic 5% · Pessimistic 8%
Score range (best/worst case)
Exposure sensitivity 23–42% · Rank sensitivity 22–38/100 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 2,749 · Median 6,080 · 75th 8,434
Evidence & sources
Data matching
direct · SSOC 13410
Real-world AI usage: -16% vs estimated
Data quality
high evidence · 4 exposure sources · direct mapping
99% weighted task match · 20% 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
- Current demand support is thin, so offsets may take longer to show up.
Worker profile & local context
- Vacancy rate is 3.4% and rose by 0.3 points from last quarter.
- Hiring read: recruitment is running above resignation (1.2% vs 0.7%).
- Retrenchment was moderate at 2.6 per 1,000 employees.
- 69.1% of retrenched workers re-entered employment within 12 months.
Worker profile
Gender mix
70% male / 30% femalePublished Singapore worker composition for the detailed occupation family 13 Production & Specialised Services Managers.
Employment structure
More self-employed79% employees, 21% employers or self-employed workers.
Work arrangement
Mostly full-time3% part-time and 97% full-time in 2025.
Age profile
Mid-career heavy2% aged 15 to 29, 58% aged 30 to 49, and 40% aged 50 or older.
Qualification mix
Degree-heavyDegree 73%; Diploma / professional qualification 14%.
Gross wage by sex
Female median 27% lowerPublished June 2024 gross wage medians: male $7,213, female $5,300.
Where this work is concentrated
Top planning areas
Bedok, Sengkang, Hougang20% 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
Shorter commutesEstimated average commute 32.0 minutes. 21% 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 Pre-school education manager?
Pre-school education manager has an AI Exposure Rank of 30/100, meaning its work is more exposed to current AI capabilities than approximately 30% 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: 30/100 (Low). Median wage: SGD 6,080/month.
What is the AI exposure rank for Pre-school education manager?
Pre-school education manager has an AI Exposure Rank of 30/100, rated Low. It ranks higher than approximately 30% of Singapore occupations for exposure to current AI capabilities; it is not a job-loss probability.
What career transitions are available for Pre-school education manager?
Pre-school education manager has modeled transition pathways to related occupations. The strongest adjacent pathway is Aged care services manager, based on skill and wage similarity (model-estimated). Transition scoring accounts for wage preservation, training ease, and destination quality.
How does Pre-school education manager salary compare in the live market?
Pre-school education manager earns a median gross wage of SGD 6,080/month in the live market (25th-75th percentile: SGD 2,749-8,434). This is 35% above median across all 562 scored occupations, and 26% below group median within Managers occupations.