Policy Analyst
Estimated role exposure score
29/100
Estimated range 17–42/100
Researches, evaluates, and recommends public or organizational policy
Policy Analyst has an estimated AI Exposure Rank of 29/100, near the 30th percentile. It is a synthetic blend of 3 occupations, not a job-loss probability.
Synthetic role estimate, not an occupation percentile rank or a prediction of job loss. Hiring, wages and role design depend on many forces that this estimate does not forecast.
Exposure estimate depends on your actual work split
Limited current buffers in the supporting context.
Built from 3 official occupations in Singapore
How This Estimate Is Built
This role-level estimate is synthesized from related occupations and a general workflow profile. It is not a percentile rank, a measured task share, or a job-loss probability.
Blended across 3 occupations using the same score logic as an occupation page. How this works
Tasks AI can handle
Running standard statistical analyses, generating charts, cleaning data, writing SQL queries, and producing summary reports from structured data.
Where humans stay essential
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.
Skills to focus on
Role profile
Heuristic workflow context blended from related occupations. This profile helps interpret the score; it is not a direct role-level measurement and is not part of the core net-risk formula.
General role profile on a 0–100 scale. These are modelling inputs, not measurements of an individual job or worker.
From exposure to employment
What could change the employment outcome?
This synthetic estimate is only a starting point. Adoption, task design, human oversight, demand, mobility and evidence quality determine what happens in practice.
Workplace adoption
Leading sectors represented
All listed industries have MOM sector adoption evidence; observed-sector average 57.5%.
Task structure
Component-derived task profile
Running standard statistical analyses, generating charts, cleaning data, writing SQL queries, and producing summary reports from structured data.
Human advantage
Coordination and judgment still matter
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.
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 0.9% time-related underemployment and 6.9% non-permanent employment. Across the published male and female series, CPI-adjusted median income changed -0.8% to +2.3% from 2018 to 2023.
Career transitions
Management consultant
easy modeled transition from the primary component occupation.
Evidence strength
high confidence
Synthetic estimate blended from 3 occupation components; it is not an official occupation statistic.
These lenses do not alter the synthetic exposure estimate. Labour indicators come from the primary component occupation's broad official cluster.
Singapore Now
Use these signals as directional context from closely related occupations and recent postings.
Observed hiring
0
30-day postings · no_signal
Employer signals
moderate
17 recent signals
Local support
1
blended context anchors
Top Industries
How this changes by career stage
What You Can Do
This estimated role shows some offset potential, but it depends on demand and transition pathways holding up across the blended occupation set.
Published transition support
Component occupation pathways
Explore each occupation for seniority and labour-market detailCompare with similar roles or occupations
Compare with... →Built From
Augmentation
Low (21%)
Dispersion
8.5pp spread · 17/100–42/100 range
Raw Scores
Exp 0.798 · Bot 0.464 · Mkt 0.580
Percentile Rank
More exposed than approximately 30% of occupations
Common tools in similar work
Blended from O*NET matches across 1 component occupations.
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.
- Employer-side pressure is still elevated in nearby functions.
Worker profile
Gender mix
50% male / 50% femalePublished Singapore worker composition for blended detailed occupation-family anchors.
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%.
Where this work is concentrated
Top planning areas
Sengkang, Bedok, Tampines19% of the blended underlying occupation families live across these three planning areas.
Residential concentration
Broadly distributed30% live across the top five planning areas in the weighted occupation blend.
Commute pattern
Mid-range commutesWeighted average commute 37.5 minutes. 33% take 46 minutes or more.
Local context & support
Market detail
Industry vacancy overlays use the latest published detailed cross-tab, which can lag the main labour monitor.
- 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.
- Employer pressure is moderate, based on 17 captured Singapore-relevant company signals through 2025-10-06.
Frequently asked questions
Will AI replace Policy Analyst?
Policy Analyst has an estimated AI Exposure Rank of 29/100, near the 30th percentile. It is a synthetic blend of 3 occupations, not a job-loss probability. Estimated role exposure score: 29/100 (Moderate).
What is the AI exposure estimate for Policy Analyst?
Policy Analyst has an estimated role exposure score of 29/100, rated Moderate. This is a synthetic estimate blending 3 official occupations in Singapore, not a job-loss probability.
What occupations make up the Policy Analyst estimate?
Policy Analyst is estimated from 3 official occupations in Singapore: Business consultant (40%), Operations research analyst (30%), Management consultant (30%).