63/100
HighHow much of this occupation’s work can be materially affected by current AI systems.
40/100
ModerateHow 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.
Task-level evidence
What is driving the score?
Occupation scores are built from the task mix—not a single prediction about a job title.
TaskImportanceAI impactExposure
Mix pesticides, herbicides, or fungicides for application to trees, shrubs, lawns, or botanical crops.High68
Lift, push, and swing nozzles, hoses, and tubes to direct spray over designated areas.High68
Fill sprayer tanks with water and chemicals, according to formulas.High68
Identify lawn or plant diseases to determine the appropriate course of treatment.High66
Cover areas to specified depths with pesticides, applying knowledge of weather conditions, droplet sizes, elevation-to-distance ratios, and obstructions.High68
Start motors and engage machinery, such as sprayer agitators or pumps or portable spray equipment.High63
Connect hoses and nozzles selected according to terrain, distribution pattern requirements, types of infestations, and velocities.High68
Clean or service machinery to ensure operating efficiency, using water, gasoline, lubricants, or hand tools.Medium23
Where AI can do more
Routine, digitized, and highly repeatable tasks face the greatest pressure.
- Mix pesticides, herbicides, or fungicides for application to trees, shrubs, lawns, or botanical crops.68
- Lift, push, and swing nozzles, hoses, and tubes to direct spray over designated areas.68
- Fill sprayer tanks with water and chemicals, according to formulas.68
- Cover areas to specified depths with pesticides, applying knowledge of weather conditions, droplet sizes, elevation-to-distance ratios, and obstructions.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.
- Clean or service machinery to ensure operating efficiency, using water, gasoline, lubricants, or hand tools.01
- Mix pesticides, herbicides, or fungicides for application to trees, shrubs, lawns, or botanical crops.02
- Lift, push, and swing nozzles, hoses, and tubes to direct spray over designated areas.03
- Fill sprayer tanks with water and chemicals, according to formulas.04
- Identify lawn or plant diseases to determine the appropriate course of treatment.05
Where else this work leads
Related occupations
Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.
Agricultural Equipment Operators
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Related work
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Shares some work
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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.
Methodology & sources
O*NET 30.3 occupational data interpreted through the JobsVsAI capability, automation and structural-constraint models.
Confidence85/100
CalculatedAug 21, 2026
Read methodology →