Urban planner
AI Exposure Rank
52/100
Range 49–62/100 across source-weight sensitivity checks
Urban planner has an AI Exposure Rank of 52/100, meaning its work is more exposed to current AI capabilities than approximately 52% of Singapore occupations. The evidence currently points to workflow redesign; this is a relative rank, not a probability of job loss.
Professionals·SGD 5,382/mo (4,382–7,500)·~2.2K 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
53% of tasks overlap with current AI
75% human advantage from judgment & presence
39% demand buffer from the local labour market
AI usage 15pp 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. How this works
Tasks AI can handle
With 53% AI task overlap (based on Felten AIOE, Anthropic Economic Index, Eloundou GPT exposure, and ILO occupational exposure), the Urban planner tasks most exposed include: running standard statistical analyses, generating charts, cleaning data, writing SQL queries, and producing summary reports from structured data.
- • Design, promote, or administer government plans or policies affecting land use, zoning, public utilities, community facilities, housing, or transportation.
- • Advise planning officials on project feasibility, cost-effectiveness, regulatory conformance, or possible alternatives.
- • Create, prepare, or requisition graphic or narrative reports on land use data, including land area maps overlaid with geographic variables, such as population density.
O*NET tasks for this occupation with the most observed AI usage (Anthropic task data).
What AI can't do here
At 75% human bottleneck protection, the tasks that remain hardest to automate for Urban planner include: framing the right question, identifying data quality issues, interpreting results in business context, communicating insights to non-technical stakeholders, and making judgment calls on methodology.
Main insulation channels: Deep preparation + 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), 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 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
Urban planner 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
Exposure-reducingHigher AI exposure, but comparatively credible exposure-reducing moves exist — the strongest scores 71% match. Escape-route quality and labour demand matter alongside exposure.
Compare within Professionals
See how this compares to similar occupations
Compare with... →Classification
More exposed than approximately 51% of occupations · V8 AI Exposure Rank· Graduate Degree
Raw scores
AIOE 0.957 · θ 0.712 · C-AIOE 0.741
Stability
stable · Optimistic 8% · Pessimistic 15%
Score range (best/worst case)
Exposure sensitivity 44–63% · Rank sensitivity 49–62/100 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 4,382 · Median 5,382 · 75th 7,500
Evidence & sources
Data matching
direct · SSOC 21641
Real-world AI usage: -15% vs estimated
Data quality
medium evidence · 4 exposure sources · direct mapping
100% weighted task match · 0% 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 3.1% 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.
- Employer pressure is low, based on 1 recent Singapore-relevant company signals.
Worker profile
Gender mix
69% male / 31% femalePublished Singapore worker composition for the detailed occupation family 21 Science & Engineering Professionals.
Employment structure
Employee-heavy96% employees, 4% employers or self-employed workers.
Work arrangement
Mostly full-time4% part-time and 96% full-time in 2025.
Age profile
Mid-career heavy14% aged 15 to 29, 62% aged 30 to 49, and 24% aged 50 or older.
Qualification mix
Degree-heavyDegree 81%; Diploma / professional qualification 15%.
Gross wage by sex
Female median 21% lowerPublished June 2024 gross wage medians: male $6,113, female $4,860.
Where this work is concentrated
Top planning areas
Sengkang, Bedok, Tampines19% 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
Mid-range commutesEstimated average commute 37.5 minutes. 33% 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 Urban planner?
Urban planner has an AI Exposure Rank of 52/100, meaning its work is more exposed to current AI capabilities than approximately 52% of Singapore occupations. The evidence currently points to workflow redesign; this is a relative rank, not a probability of job loss. AI Exposure Rank: 52/100 (Moderate). Median wage: SGD 5,382/month.
What is the AI exposure rank for Urban planner?
Urban planner has an AI Exposure Rank of 52/100, rated Moderate. It ranks higher than approximately 52% of Singapore occupations for exposure to current AI capabilities; it is not a job-loss probability.
What career transitions are available for Urban planner?
Urban planner has modeled transition pathways to related occupations. The strongest adjacent pathway is Commercial airline pilot, based on skill and wage similarity (model-estimated). Transition scoring accounts for wage preservation, training ease, and destination quality.
How does Urban planner salary compare in the live market?
Urban planner earns a median gross wage of SGD 5,382/month in the live market (25th-75th percentile: SGD 4,382-7,500). This is 20% above median across all 562 scored occupations, and 17% below group median within Professionals occupations.