Building and Grounds Cleaning and Maintenance · United States (national)
First-Line Supervisors of Landscaping, Lawn Service, and Groundskeeping Workers
How exposed this work is to automation, shown as ranges with the reasoning and sources.
The short version: this role is moderately exposed to automation, and meaningful change looks likely over the next 5 to 10 years.
It is a sourced range, not a verdict, and the detail is below.
Built on O*NET tasks, BLS pay and projections, and peer-reviewed AI-exposure research. Sources shown.
Data snapshot SNAPSHOT-2026-11-06. How it works
AI / softwarerange 12.6 to 36.6
Physical / roboticsrange 46.5 to 70.5
When the change is likely
Partial, 5 to 10 yearslocal demand stable
What to do about it
Use AI to outpace AI.
Strategies to protect your livelihood, most important first.
1
Use your 5 to 10 year runway
Change here is gradual. Build resilient skills steadily and watch the signals rather than waiting for a shock.
2
Move up from the task to the system
Robotics targets the physical work. Shift toward supervising, maintaining, or programming the automation instead of competing with it.
3
Pivot toward First-Line Supervisors of Entertainment and Recreation Workers, Except Gambling Services
It is skill-adjacent and less exposed (34.2 vs 58). A lateral move now beats a forced one later.
4
Build a financial buffer
Keep 6 to 12 months of expenses and diversify your income, so a disruption is a setback rather than a catastrophe.
5
Add a recognised credential
A certification or license raises the bar against automation and signals value in a tightening market.
Keep the monitor on
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Which of my tasks are exposed
Establish and enforce operating procedures and work standards that will ensure adequate performance and personnel safety.
58.5
Schedule work for crews, depending on work priorities, crew or equipment availability, or weather conditions.
58.5
Tour grounds, such as parks, botanical gardens, cemeteries, or golf courses, to inspect conditions of plants and soil.
100.0
Monitor project activities to ensure that instructions are followed, deadlines are met, and schedules are maintained.
58.5
Direct activities of workers who perform duties, such as landscaping, cultivating lawns, or pruning trees and shrubs.
58.5
Inspect completed work to ensure conformance to specifications, standards, and contract requirements.
58.5
Plant or maintain vegetation through activities such as mulching, fertilizing, watering, mowing, or pruning.
58.5
Direct or perform mixing or application of fertilizers, insecticides, herbicides, or fungicides.
58.5
Longer, orange bars are more automatable; short green bars are resistant.
What is driving my result
lowers risk
raises risk
Task: Tour grounds, such as parks, botanical gardens, cemeteries, or golf courses, to inspect conditions of plants and soil.
Task: Establish and enforce operating procedures and work standards that will ensure adequate performance and personnel safety.
Lower-risk adjacent roles
First-Line Supervisors of Entertainment and Recreation Workers, Except Gambling Services
34.2
First-Line Supervisors of Housekeeping and Janitorial Workers
46.9
First-Line Supervisors of Material-Moving Machine and Vehicle Operators
47.1
First-Line Supervisors of Mechanics, Installers, and Repairers
47.2
First-Line Supervisors of Farming, Fishing, and Forestry Workers
47.5
First-Line Supervisors of Construction Trades and Extraction Workers
55.0
A full, ranked mitigation plan is part of the paid tiers.
How this score is calculated
Map First-Line Supervisors of Landscaping, Lawn Service, and Groundskeeping Workers to its standard O*NET task list (8 core tasks).
Score each task for AI/software exposure (Eloundou et al. 2023) and physical/robotics exposure (an O*NET work-context proxy), each 0 to 100.
The two axis scores are the task averages: AI 24.6, robotics 58.5.
The timeline comes from the higher axis (58.5), shifted for local demand (stable), and seniority. It is read against your remaining working years.
Ranges are about ±12 points. A backtest against real BLS employment change shows the risk ranking holds in aggregate, but individual outcomes are predicted weakly, so results are ranges, never a flat verdict.
Sources: O*NET, Eloundou et al. (2023), GPTs are GPTs, O*NET Work Context, BLS CPI-U, BLS OEWS.
Snapshot SNAPSHOT-2026-11-06. Full method and backtest on How it works.