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AI Work Index

Hair stylist/Hairdresser

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AI Exposure Rank

13/100

Very Low

Range 11–18/100 across source-weight sensitivity checks

Hair stylist/Hairdresser has an AI Exposure Rank of 13/100, meaning its work is more exposed to current AI capabilities than approximately 13% of Singapore occupations. The evidence currently points to limited direct change; this is a relative rank, not a probability of job loss.

Limited direct change

Service & Sales Workers·SGD 3,756/mo (2,915–4,773)·~3.5K 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 26% above group median Exposure 10pp below group median #32 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 18% AI task overlap (based on Felten AIOE, Anthropic Economic Index, Eloundou GPT exposure, and ILO occupational exposure), the Hair stylist/Hairdresser tasks most exposed include: reservation management, menu recommendations, order processing, loyalty program tracking, and basic customer query handling via chatbots.

  • • Schedule client appointments.
  • • Keep work stations clean and sanitize tools, such as scissors and combs.
  • • Bleach, dye, or tint hair, using applicator or brush.

O*NET tasks for this occupation with the most observed Claude usage (Anthropic task data).

What AI can't do here

At 45% human bottleneck protection, the tasks that remain hardest to automate for Hair stylist/Hairdresser 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

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

Occupation-level adoption unknown

MOM does not publish a directly mappable adoption rate for the listed industries.

02

Task structure

Task evidence available

100% weighted task match · 7% effective coverage

03

Human advantage

Coordination and judgment still matter

At 45% human bottleneck protection, the tasks that remain hardest to automate for Hair stylist/Hairdresser 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

Slimming consultant

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

06

Evidence strength

medium confidence

4 exposure sources · sensitivity 11–18/100 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 Hair stylist/Hairdresser?

Hair stylist/Hairdresser has an AI Exposure Rank of 13/100, meaning its work is more exposed to current AI capabilities than approximately 13% 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: 13/100 (Very Low). Median wage: SGD 3,756/month.

What is the AI exposure rank for Hair stylist/Hairdresser?

Hair stylist/Hairdresser has an AI Exposure Rank of 13/100, rated Very Low. It ranks higher than approximately 13% of Singapore occupations for exposure to current AI capabilities; it is not a job-loss probability.

What career transitions are available for Hair stylist/Hairdresser?

Hair stylist/Hairdresser has modeled transition pathways to related occupations. The strongest adjacent pathway is Slimming consultant, based on skill and wage similarity (model-estimated). Transition scoring accounts for wage preservation, training ease, and destination quality.

How does Hair stylist/Hairdresser salary compare in the live market?

Hair stylist/Hairdresser earns a median gross wage of SGD 3,756/month in the live market (25th-75th percentile: SGD 2,915-4,773). This is 17% below median across all 562 scored occupations, and 26% above group median within Service & Sales Workers occupations.