Pre-primary education teacher
AI Exposure Rank
16/100
Range 6–23/100 across source-weight sensitivity checks
Pre-primary education teacher has an AI Exposure Rank of 16/100, meaning its work is more exposed to current AI capabilities than approximately 16% of Singapore occupations. The evidence currently points to limited direct change; this is a relative rank, not a probability of job loss.
Associate Professionals & Technicians·SGD 4,000/mo (3,600–4,800)·~7.4K 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
21% of tasks overlap with current AI
70% human advantage from judgment & presence
39% demand buffer from the local labour market
AI usage 28pp 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 21% AI task overlap (based on Felten AIOE, Anthropic Economic Index, and Eloundou GPT exposure), the Pre-primary education teacher tasks most exposed include: generating lesson plans, creating quizzes and practice exercises, summarizing curricula, personalizing reading lists, and grading objective assessments.
- • Evaluate and grade students' class work, assignments, and papers.
- • Conduct research in a particular field of knowledge and publish findings in professional journals, books, or electronic media.
- • Compile, administer, and grade examinations, or assign this work to others.
O*NET tasks for this occupation with the most observed AI usage (Anthropic task data).
What AI can't do here
At 70% human bottleneck protection, the tasks that remain hardest to automate for Pre-primary education teacher 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: Non-routine work + Relational 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.
Singapore Now
Current labour market conditions and how they affect this role.
Cooling, but not collapsing. Vacancies and re-entry are softer, yet retrenchment remains low and hiring still exceeds resignations.
Vacancy
3.1%
↓ 3.1% YoY
Hiring
1.5%
vs 0.9% resign
Retrenchment
1.5
per 1,000 · low
Re-entry
67.7%
find work in 12mo· -5.3pp
Professionals, Managers, Executives & Technicians · 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
Pre-primary education teacher 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 Associate Professionals & Technicians
See how this compares to similar occupations
Compare with... →Classification
More exposed than approximately 16% of occupations · V8 AI Exposure Rank· University Degree
Raw scores
AIOE 0.198 · θ 0.706 · C-AIOE 0.154
Stability
watch · Optimistic 3% · Pessimistic 7%
Score range (best/worst case)
Exposure sensitivity 10–31% · Rank sensitivity 6–23/100 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 3,600 · Median 4,000 · 75th 4,800
Evidence & sources
Data matching
direct · SSOC 36100
Real-world AI usage: -28% vs estimated
Data quality
medium evidence · 3 exposure sources · direct mapping
100% weighted task match · 33% effective coverage
AI overlap by data source
Weights: aioe 32% · anthropic 35% · eloundou 33%
Conflicting data signals
Tools & offset factors
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 was essentially flat versus last quarter.
- Hiring read: recruitment is running above resignation (1.5% vs 0.9%).
- Retrenchment was low at 1.5 per 1,000 employees.
- 67.7% of retrenched workers re-entered employment within 12 months.
Worker profile
Gender mix
16% male / 84% femalePublished Singapore worker composition for the detailed occupation family 36 Teaching Associate Professionals.
Employment structure
Employee-heavy87% employees, 13% employers or self-employed workers.
Work arrangement
Mostly full-time9% part-time and 91% full-time in 2025.
Age profile
Mid-career heavy17% aged 15 to 29, 52% aged 30 to 49, and 31% aged 50 or older.
Qualification mix
Diploma-heavyDegree 37%; Diploma / professional qualification 35%.
Gross wage by sex
Female median 5% higherPublished June 2024 gross wage medians: male $3,800, female $4,000.
Where this work is concentrated
Top planning areas
Jurong West, Woodlands, Tampines22% 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 38.7 minutes. 36% 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 Pre-primary education teacher?
Pre-primary education teacher has an AI Exposure Rank of 16/100, meaning its work is more exposed to current AI capabilities than approximately 16% 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: 16/100 (Very Low). Median wage: SGD 4,000/month.
What is the AI exposure rank for Pre-primary education teacher?
Pre-primary education teacher has an AI Exposure Rank of 16/100, rated Very Low. It ranks higher than approximately 16% of Singapore occupations for exposure to current AI capabilities; it is not a job-loss probability.
What career transitions are available for Pre-primary education teacher?
Pre-primary education teacher has modeled transition pathways to related occupations. The strongest adjacent pathway is Private tutor (academic), based on skill and wage similarity (model-estimated). Transition scoring accounts for wage preservation, training ease, and destination quality.
How does Pre-primary education teacher salary compare in the live market?
Pre-primary education teacher earns a median gross wage of SGD 4,000/month in the live market (25th-75th percentile: SGD 3,600-4,800). This is 11% below median across all 562 scored occupations, and 3% below group median within Associate Professionals & Technicians occupations.