Tea server/steward (excluding bartender, barista and food/drink stall assistant)
AI Exposure Rank
18/100
Range 8–27/100 across source-weight sensitivity checks
Tea server/steward (excluding bartender, barista and food/drink stall assistant) has an AI Exposure Rank of 18/100, meaning its work is more exposed to current AI capabilities than approximately 18% of Singapore occupations. The evidence currently points to limited direct change; this is a relative rank, not a probability of job loss.
Cleaners, Labourers & Related Workers·SGD 1,725/mo (1,570–2,084)·~8.9K 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 22% AI task overlap (based on Felten AIOE, Anthropic Economic Index, and Eloundou GPT exposure), the Tea server/steward (excluding bartender, barista and food/drink stall assistant) tasks most exposed include: reservation management, menu recommendations, order processing, loyalty program tracking, and basic customer query handling via chatbots.
- • Place food servings on plates or trays according to orders or instructions.
- • Clean or sterilize dishes, kitchen utensils, equipment, or facilities.
- • Monitor food distribution, ensuring that meals are delivered to the correct recipients and that guidelines, such as those for special diets, are followed.
O*NET tasks for this occupation with the most observed Claude usage (Anthropic task data).
What AI can't do here
At 6% human bottleneck protection, the tasks that remain hardest to automate for Tea server/steward (excluding bartender, barista and food/drink stall assistant) include: genuine hospitality and warmth, reading customer moods, handling complaints gracefully, creating memorable experiences, and adapting service to cultural expectations.
Main insulation channels: Non-routine work + High-stakes decisions — the work-context dimensions behind this occupation's human bottleneck.
Skills to focus on
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), 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
Leading sectors represented
Some listed industries have MOM sector adoption evidence; observed-sector average 57.5%.
Task structure
Task evidence limited
100% weighted task match · 0% effective coverage
Human advantage
Coordination and judgment still matter
At 6% human bottleneck protection, the tasks that remain hardest to automate for Tea server/steward (excluding bartender, barista and food/drink stall assistant) include: genuine hospitality and warmth, reading customer moods, handling complaints gracefully, creating memorable experiences, and adapting service to cultural expectations.
Hiring and demand
2.3% vacancy rate · 2026 Q1
Production and transport vacancies fell back from the Q4 spike and were slightly below a year earlier. Hiring remained net positive, retrenchments declined, and six-month re-entry improved. In 2025, this broad occupation group had 4.9% time-related underemployment and 19.2% non-permanent employment. Across the published male and female series, CPI-adjusted median income changed +0.2% to +8.6% from 2018 to 2023.
Career transitions
Wellness centre manager (e.g. hair/beauty/slimming/spa/manicure/massage)
moderate modeled transition; outcomes still depend on skills, wages and openings.
Evidence strength
medium confidence
3 exposure sources · sensitivity 8–27/100 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.
Cooling, but not collapsing. Vacancies are softer, yet retrenchment remains low and hiring still exceeds resignations.
Vacancy
2.3%
↓ 4.2% YoY
Hiring
1.7%
vs 1.2% resign
Retrenchment
0.3
per 1,000 · low
Re-entry
76.9%
find work in 12mo· -1.2pp
Production & Transport Operators, Cleaners & Labourers · 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
Tea server/steward (excluding bartender, barista and food/drink stall assistant) has some offset potential, but it depends on transition pathways holding up in practice and on workers clearing the main switching frictions.
Published transition support
Related roles you could transition to
Similarity-basedCompare within Cleaners, Labourers & Related Workers
See how this compares to similar occupations
Compare with... →Classification
More exposed than approximately 18% of occupations · V8 AI Exposure Rank· GCE O-Level / Secondary
Raw scores
AIOE -0.641 · θ 0.586 · C-AIOE -0.577
Stability
watch · Optimistic 9% · Pessimistic 20%
Score range (best/worst case)
Exposure sensitivity 8–35% · Rank sensitivity 8–27/100 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 1,570 · Median 1,725 · 75th 2,084
Evidence & sources
Data matching
direct · SSOC 94104
Real-world AI usage: +28% vs estimated
Data quality
medium evidence · 3 exposure sources · direct mapping
100% weighted task match · 0% effective coverage
AI overlap by data source
Weights: aioe 32% · anthropic 35% · eloundou 33%
Conflicting data signals
Worker profile & local context
- Vacancy rate is 2.3% and fell by 0.5 points from last quarter.
- Hiring read: recruitment is running above resignation (1.7% vs 1.2%).
- Retrenchment was low at 0.3 per 1,000 employees.
- 76.9% of retrenched workers re-entered employment within 12 months.
Worker profile
Gender mix
32% male / 68% femalePublished Singapore worker composition for the detailed occupation family 94 Food Preparation & Kitchen Assistants.
Employment structure
Employee-heavy96% employees, 4% employers or self-employed workers.
Work arrangement
Part-time meaningful33% part-time and 67% full-time in 2025.
Age profile
Older-skewing5% aged 15 to 29, 14% aged 30 to 49, and 81% aged 50 or older.
Qualification mix
Non-degree heavyBelow secondary 56%; Secondary 18%.
Gross wage by sex
Female median 37% lowerPublished June 2024 gross wage medians: male $2,656, female $1,670.
Where this work is concentrated
Top planning areas
Jurong West, Woodlands, Bedok22% 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
Mid-range commutesEstimated average commute 32.8 minutes. 27% 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 Tea server/steward (excluding bartender, barista and food/drink stall assistant)?
Tea server/steward (excluding bartender, barista and food/drink stall assistant) has an AI Exposure Rank of 18/100, meaning its work is more exposed to current AI capabilities than approximately 18% 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: 18/100 (Very Low). Median wage: SGD 1,725/month.
What is the AI exposure rank for Tea server/steward (excluding bartender, barista and food/drink stall assistant)?
Tea server/steward (excluding bartender, barista and food/drink stall assistant) has an AI Exposure Rank of 18/100, rated Very Low. It ranks higher than approximately 18% of Singapore occupations for exposure to current AI capabilities; it is not a job-loss probability.
What career transitions are available for Tea server/steward (excluding bartender, barista and food/drink stall assistant)?
Tea server/steward (excluding bartender, barista and food/drink stall assistant) has modeled transition pathways to related occupations. The strongest adjacent pathway is Child/After school care centre worker, based on skill and wage similarity (model-estimated). Transition scoring accounts for wage preservation, training ease, and destination quality.
How does Tea server/steward (excluding bartender, barista and food/drink stall assistant) salary compare in the live market?
Tea server/steward (excluding bartender, barista and food/drink stall assistant) earns a median gross wage of SGD 1,725/month in the live market (25th-75th percentile: SGD 1,570-2,084). This is 62% below median across all 562 scored occupations, and 11% below group median within Cleaners, Labourers & Related Workers occupations.