Skip to content
AI Work Index

Cook (e.g. commis cook 2/3)

Compare

AI Exposure Rank

23/100

Low

Range 18–31/100 across source-weight sensitivity checks

Cook (e.g. commis cook 2/3) has an AI Exposure Rank of 23/100, meaning its work is more exposed to current AI capabilities than approximately 23% of Singapore occupations. The evidence currently points to limited direct change; this is a relative rank, not a probability of job loss.

Limited direct changeClassification uncertain

Service & Sales Workers·SGD 2,028/mo (1,500–2,955)·~2.6K 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.

Wage 32% below group median Exposure near group median #23 of 45 in Service & Sales Workers →
01

How This Rank Is Built

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 26% AI task overlap (based on Felten AIOE, Anthropic Economic Index, Eloundou GPT exposure, and ILO occupational exposure), the Cook (e.g. commis cook 2/3) tasks most exposed include: reservation management, menu recommendations, order processing, loyalty program tracking, and basic customer query handling via chatbots.

What AI can't do here

At 15% human bottleneck protection, the tasks that remain hardest to automate for Cook (e.g. commis cook 2/3) include: genuine hospitality and warmth, reading customer moods, handling complaints gracefully, creating memorable experiences, and adapting service to cultural expectations.

Main insulation channels: Accountability for others + Non-routine work — the work-context dimensions behind this occupation's human bottleneck.

Skills to focus on

Emotional IntelligenceConflict De-escalationCultural SensitivityExperience Crafting

Brynjolfsson et al. (2023) found customer service agents using AI saw +14% productivity, with the biggest gains among junior workers — AI compressed the experience gap.

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.

01

Workplace adoption

Leading sectors represented

Some listed industries have MOM sector adoption evidence; observed-sector average 57.5%.

02

Task structure

Task evidence limited

Task-weighted shadow evidence is not active for this occupation yet.

03

Human advantage

Coordination and judgment still matter

At 15% human bottleneck protection, the tasks that remain hardest to automate for Cook (e.g. commis cook 2/3) include: genuine hospitality and warmth, reading customer moods, handling complaints gracefully, creating memorable experiences, and adapting service to cultural expectations.

04

Hiring and demand

3.2% vacancy rate · 2026 Q1

Clerical, sales and service vacancies recovered slightly from Q4 but remained well below a year earlier. Hiring turnover slowed, retrenchment incidence stayed low, and six-month re-entry improved. In 2025, this broad occupation group had 4.0% time-related underemployment and 16.0% non-permanent employment. Across the published male and female series, CPI-adjusted median income changed -1.9% to -0.1% from 2018 to 2023.

05

Career transitions

Senior cook (e.g. station chef, commis cook 1, station cook)

moderate modeled transition; outcomes still depend on skills, wages and openings.

06

Evidence strength

medium confidence

4 exposure sources · sensitivity 18–31/100 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.

02

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

3.2%

↓ 20.0% YoY

Hiring

2.1%

vs 1.4% resign

Retrenchment

0.7

per 1,000 · low

Re-entry

68%

find work in 12mo· -10.5pp

Clerical, Sales & Service Workers · 2026 Q1

Top Industries

Accommodation & Food Services
26%
Wholesale & Retail Trade
25%
Administrative & Support Services
13%

Industry vacancy overlays use the latest published detailed cross-tab, which can lag the main labour monitor.

03

What You Can Do

Frequently asked questions

Will AI replace Cook (e.g. commis cook 2/3)?

Cook (e.g. commis cook 2/3) has an AI Exposure Rank of 23/100, meaning its work is more exposed to current AI capabilities than approximately 23% 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: 23/100 (Low). Median wage: SGD 2,028/month.

What is the AI exposure rank for Cook (e.g. commis cook 2/3)?

Cook (e.g. commis cook 2/3) has an AI Exposure Rank of 23/100, rated Low. It ranks higher than approximately 23% of Singapore occupations for exposure to current AI capabilities; it is not a job-loss probability.

What career transitions are available for Cook (e.g. commis cook 2/3)?

Cook (e.g. commis cook 2/3) has modeled transition pathways to related occupations. The strongest adjacent pathway is Senior cook (e.g. station chef, commis cook 1, station cook), based on skill and wage similarity (model-estimated). Transition scoring accounts for wage preservation, training ease, and destination quality.

How does Cook (e.g. commis cook 2/3) salary compare in the live market?

Cook (e.g. commis cook 2/3) earns a median gross wage of SGD 2,028/month in the live market (25th-75th percentile: SGD 1,500-2,955). This is 55% below median across all 562 scored occupations, and 32% below group median within Service & Sales Workers occupations.