How much of this occupation’s work can be materially affected by current AI systems.
How likely exposure is to translate into reduced human demand.
Includes provisional estimates for AI adoption pressure and labour-market resilience. How this is measured
Confidence reflects task coverage, mapping and capability-evidence quality, and how much of the score rests on provisional inputs.
What is driving the score?
Occupation scores are built from the task mix—not a single prediction about a job title.
Where AI can do more
Routine, digitized, and highly repeatable tasks face the greatest pressure.
- Direct activities of workers who perform duties, such as landscaping, cultivating lawns, or pruning trees and shrubs.68
- Establish and enforce operating procedures and work standards that will ensure adequate performance and personnel safety.68
- Provide workers with assistance in performing duties as necessary to meet deadlines.68
- Identify diseases or pests affecting landscaping and order appropriate treatments.68
Where people still matter
These tasks score lowest on automation feasibility—physical presence, judgement, accountability and real-world variability all resist end-to-end automation.
- Install or maintain landscaped areas, performing tasks such as removing snow, pouring cement curbs, or repairing sidewalks.01
- Direct or assist workers engaged in the maintenance or repair of equipment, such as power tools or motorized equipment.02
- Direct activities of workers who perform duties, such as landscaping, cultivating lawns, or pruning trees and shrubs.03
- Schedule work for crews, depending on work priorities, crew or equipment availability, or weather conditions.04
- Establish and enforce operating procedures and work standards that will ensure adequate performance and personnel safety.05
Related occupations
Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.
First-Line Supervisors of Construction Trades and Extraction Workers
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Related work
Compare these careers →Adoption and labour-market outlook
Structural factors are kept separate from raw capability so you can see what actually resists automation. Adoption pressure and labour-market resilience are still provisional models—25% of this occupation’s replacement-risk weight rests on them.
O*NET 30.3 occupational data interpreted through the JobsVsAI capability, automation and structural-constraint models.
