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Will AI replace Grounds Maintenance Workers, All Other?

All grounds maintenance workers not listed separately. The percentage shown is a task-exposure model, not a prediction of certain job loss.

O*NET 30.3 · 37-3019.00 · modeled exposure, not guaranteed job loss
LOW TASK EXPOSURE
31%
Estimated share of representative tasks exposed to current AI capabilities.
Task automation shareⓘ
31%Automatable
Automatable31%
Augmentable38%
Hard to automate31%
Based on analysis of representative responsibilities and current AI capability maturity.
Category#
Trades & Physical
Field & Physical
Modeled pay midpoint$
$83,300/yr
Directional estimate — verify locally
Time until impact⌁
6–10+ years
Earliest 2032 · widespread 2036+
Task-level replaceability ⓘ
Representative tasks ranked from highest to lowest AI exposure.
◇Organize role-specific information and routine work41%
⚙Prepare standard outputs and records28%
✦Physical dexterity in unpredictable settings23%
✦Safety responsibility and on-site judgment19%
Impact timeline ⓘ
How AI assistance may move from early support to wider adoption.
2032Next2036+
Light supportAI provides limited help with organize role-specific information and routine work.
AugmentationTools improve productivity without owning outcomes.
Human-ledCore work stays anchored in physical dexterity in unpredictable settings.
6–10+ yearsdirectional confidence window
HOW AI CHANGES THIS JOBtyping the logic in plain English
01>Start with the real work done by Grounds Maintenance Workers, All Other.
02>AI can help with: Organize role-specific information and routine work.
03>If a task is repetitive and easy to check, AI pressure goes up.
04>But a person is still needed for: Physical dexterity in unpredictable settings.
05>Likely result: AI mostly acts as a helper while the core job stays human-led.
06>Important: 31% is estimated task exposure—not a 31% chance of losing the job.
What AI can do
Organize role-specific information and routine workLOW MATCH
Prepare standard outputs and recordsLOW MATCH
How estimates work →
Your human moat
◆

Physical dexterity in unpredictable settings

HIGH MOAT

Combined with safety responsibility and on-site judgment, this keeps a human in the loop.

Strength8.7
Similar-role comparison
RoleRisk
Grounds Maintenance Workers, All Other31%
Building Cleaning Workers, All Other30%
Landscaping and Groundskeeping Workers32%
Pesticide Handlers, Sprayers, and Applicators, Vegetation30%
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Why this score?

✓The model evaluates 2 representative core tasks.
✓The core work depends on presence, dexterity, or accountability.
✓Occupation and task language comes from O*NET 30.3.
✓The strongest human advantage is physical dexterity in unpredictable settings.
Research basis

O*NET 30.3 occupation tasks plus the ILO 2025 exposure framework. Scores are directional estimates.

Read ILO research →
Data: O*NET 30.3 · Model framework: ILO 2025About O*NETShare report
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Related Trades & Physical job reports

Building Cleaning Workers, All Other · 30% exposureLandscaping and Groundskeeping Workers · 32% exposurePesticide Handlers, Sprayers, and Applicators, Vegetation · 30% exposure