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AI Automation Index
Will AI Replace Pesticide Handlers, Sprayers, and Applicators, Vegetation?
Task-level automation exposure for Pesticide Handlers, Sprayers, and Applicators, Vegetation: 12 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
25%
weighted task index
12 of 12 tasks scored
Median Salary
$46,340 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
Medium
27,050 people hold this job — size, not growth
Projected 2025–35
+3.9%
employment change
3,300 openings a year · BLS line item
Pay by state
BLS OEWS publishes 44 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$26,220 – $62,980
Highest medians
Massachusetts $62,980
Delaware $54,190
Oregon $51,590
Hawaii $51,240
North Dakota $50,490
Lowest medians
Louisiana $26,220
Mississippi $35,770
Oklahoma $36,870
Montana $37,760
Arkansas $37,860
State figures come from the 37-3012 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.
What the score is made of
Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.
Automation potential 25%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 70%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 12%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 11%
Share in documenting, recording, and administrative activities.
Rewritten by O*NET 0%
Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.
Consequence of error 1/100
Low
O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.
Constituent Task Mix
12 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.
High exposure (≥ 60% of the task is automatable) 20%
2 tasks
Medium exposure (≥ 35%) 3%
1 tasks
Low exposure (below 35%) 77%
9 tasks
How would you survive?
Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.
Simulate Upskilling →Emerging & rewritten tasks
Tasks O*NET added or rewrote for this occupation in its recent updates (05/2025 – 08/2026), with who proposed them. Additions are not in the scored task inventory — they are new work O*NET is still measuring, so they appear here and nowhere in the index. A Revision replaces a task that is scored, which is why only those move the "Rewritten by O*NET" share.
- New 05/2025 · AI/SME
Use new technology and equipment, such as drones or GPS systems, to apply pesticides more accurately and efficiently.
Constituent Tasks
#11227 · Core · 15% automatable
Fill sprayer tanks with water and chemicals, according to formulas.
physical manipulation — Chemical preparation requires hands-on handling
Prepare chemicals for work application.
#24043 · Core · 79% automatable
Record information about pesticide applications, such as the type used and amount applied.
data analysis — Maintain operational records in structured systems
Document operational procedures. Maintain operational records.
#11228 · Core · 15% automatable
Mix pesticides, herbicides, or fungicides for application to trees, shrubs, lawns, or botanical crops.
physical manipulation — Chemical preparation requires hands-on handling
Prepare chemicals for work application.
#11231 · Core · 10% automatable
Start motors and engage machinery, such as sprayer agitators or pumps or portable spray equipment.
situated mobility — Grounds equipment operation needs real-world control
Operate grounds maintenance equipment.
#11230 · Core · 10% automatable
Lift, push, and swing nozzles, hoses, and tubes to direct spray over designated areas.
physical manipulation — Treating greenery is physical application work
Treat greenery or surfaces with protective substances.
#24044 · Core · 61% automatable
Establish driving routes for pesticide applications.
data analysis — Route optimization computational; human confirms
Choose optimal transportation routes or speeds. Establish operational policies.
#11233 · Core · 8% automatable
Clean or service machinery to ensure operating efficiency, using water, gasoline, lubricants, or hand tools.
physical manipulation — Hands-on system maintenance to ensure function
Clean equipment or supplies. Maintain equipment or systems to ensure proper functioning.
#11232 · Core · 10% automatable
Connect hoses and nozzles selected according to terrain, distribution pattern requirements, types of infestations, and velocities.
situated mobility — Grounds equipment operation needs real-world control
Operate grounds maintenance equipment.
#11229 · Core · 10% automatable
Cover areas to specified depths with pesticides, applying knowledge of weather conditions, droplet sizes, elevation-to-distance ratios, and obstructions.
physical manipulation — Treating greenery is physical application work
Treat greenery or surfaces with protective substances.
#20762 · Supplemental · 30% automatable
Identify lawn or plant diseases to determine the appropriate course of treatment.
visual inspection — Landscape inspection needs on-site visual assessment
Inspect landscaping to determine treatment needs.
#11235 · Supplemental · 7% automatable
Plant grass with seed spreaders, and operate straw blowers to cover seeded areas with mixtures of asphalt and straw.
situated mobility — Grounds equipment operation needs real-world control
Plant greenery to improve landscape appearance. Operate grounds maintenance equipment.
#11234 · Supplemental · 45% automatable
Provide driving instructions to truck drivers to ensure complete coverage of designated areas, using hand and horn signals.
interpersonal — Policy instruction content aided, delivery human
Instruct staff in work policies or procedures.
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How this was scored
- 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
- 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
- 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
- 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.
Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.
Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast
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