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AI Work Index

Landscape worker

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AI Exposure Rank

1/100

Very Low

Range 0–2/100 across source-weight sensitivity checks

Landscape worker has an AI Exposure Rank of 1/100, meaning its work is more exposed to current AI capabilities than approximately 1% 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

Cleaners, Labourers & Related Workers·SGD 1,800/mo (1,750–1,902)·~500 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 7% below group median Exposure 4pp below group median #33 of 40 in Cleaners, Labourers & Related 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 6% AI task overlap (based on Felten AIOE, Anthropic Economic Index, Eloundou GPT exposure, and ILO occupational exposure), the Landscape worker tasks most exposed include: predictive maintenance scheduling, safety checklist automation, inventory management, and remote monitoring via sensors.

  • • Confer with clients, engineering personnel, or architects on landscape projects.
  • • Analyze data on conditions such as site location, drainage, or structure location for environmental reports or landscaping plans.
  • • Inspect landscape work to ensure compliance with specifications, evaluate quality of materials or work, or advise clients or construction personnel.

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

What AI can't do here

At 22% human bottleneck protection, the tasks that remain hardest to automate for Landscape worker include: physical dexterity on job sites, real-time environmental adaptation, operating heavy equipment safely, and handling unexpected on-site conditions.

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

Skills to focus on

Hands-On ExpertiseOn-Site Problem SolvingSafety ProtocolsEquipment Proficiency

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 limited

100% weighted task match · 0% effective coverage

03

Human advantage

Coordination and judgment still matter

At 22% human bottleneck protection, the tasks that remain hardest to automate for Landscape worker include: physical dexterity on job sites, real-time environmental adaptation, operating heavy equipment safely, and handling unexpected on-site conditions.

04

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.

05

Career transitions

Tree worker/technician

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

06

Evidence strength

medium confidence

4 exposure sources · sensitivity 0–2/100 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 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

Public Administration & Education Services
31%
Administrative & Support Services
23%
Accommodation & Food Services
23%

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 Landscape worker?

Landscape worker has an AI Exposure Rank of 1/100, meaning its work is more exposed to current AI capabilities than approximately 1% 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: 1/100 (Very Low). Median wage: SGD 1,800/month.

What is the AI exposure rank for Landscape worker?

Landscape worker has an AI Exposure Rank of 1/100, rated Very Low. It ranks higher than approximately 1% of Singapore occupations for exposure to current AI capabilities; it is not a job-loss probability.

What career transitions are available for Landscape worker?

Landscape worker has modeled transition pathways to related occupations. The strongest adjacent pathway is Tree worker/technician, based on skill and wage similarity (model-estimated). Transition scoring accounts for wage preservation, training ease, and destination quality.

How does Landscape worker salary compare in the live market?

Landscape worker earns a median gross wage of SGD 1,800/month in the live market (25th-75th percentile: SGD 1,750-1,902). This is 60% below median across all 562 scored occupations, and 7% below group median within Cleaners, Labourers & Related Workers occupations.