Last Update: 2/18/2026
Your role’s AI Resilience Score is
Median Score
Changing Fast
Evolving
Stable
This reflects the reliability of your score based on the number of data sources available for this career and how closely those sources agree on the outlook. A higher confidence means more consistent evidence from labor experts and AI models.
What does this resilience result mean?
These roles are shifting as AI becomes part of everyday workflows. Expect new responsibilities and new opportunities.
AI Resilience Report for
They protect plants by safely applying chemicals to control pests and diseases, ensuring crops and landscapes stay healthy.
This role is evolving
This career is labeled as "Evolving" because AI and robots are being integrated to handle the toughest and most precise tasks, like large-area spraying, which helps save time and chemicals. However, human skills are still essential for planning, mixing chemicals, spotting diseases, and making careful judgments about plant health.
Read full analysisLearn more about how you can thrive in this position
Learn more about how you can thrive in this position
This role is evolving
This career is labeled as "Evolving" because AI and robots are being integrated to handle the toughest and most precise tasks, like large-area spraying, which helps save time and chemicals. However, human skills are still essential for planning, mixing chemicals, spotting diseases, and making careful judgments about plant health.
Read full analysisContributing Sources
We aggregate scores from multiple models and supplement with employment projections for a more accurate picture of this occupation’s resilience. Expand to view all sources.
AI Resilience
AI Resilience Model v1.0
AI Task Resilience
Microsoft's Working with AI
AI Applicability
Will Robots Take My Job
Automation Resilience
Medium Demand
We use BLS employment projections to complement the AI-focused assessments from other sources.
Learn about this scoreGrowth Rate (2024-34):
Growth Percentile:
Annual Openings:
Annual Openings Pct:
Analysis of Current AI Resilience
Pesticide Handlers
Updated Quarterly • Last Update: 2/18/2026

What's changing and what's not
Today, farmers use some high-tech helpers but much of the work still needs people. For example, applicators now sometimes use GPS-guided tractors and even drone sprayers. One company’s autonomous eVTOL drone (approved by the FAA) can carry 200 pounds of spray and cover 60 acres in an hour [1].
Research robots can already recognize weeds in a vineyard and target-spray them, cutting pesticide use by 65–85% [2]. Even the O*NET description of the job notes that workers “use… drones or GPS systems” to improve spraying accuracy [3]. Experiments also show machines that zap weeds with lasers and AI cameras – truly sci-fi stuff – can kill thousands of weeds per minute without chemicals [4].
However, most core tasks remain human-led. Workers still mix chemicals by hand in tanks, start the sprayer engine, and physically aim hoses over lawns and bushes. No robot yet can climb a tree and judge a plant’s health quite as well as a trained applicator.
On the good side, AI tools are helping. For instance, smartphone apps now let a user snap a photo of a sick plant and get an instant diagnosis or treatment advice [5]. These tools augment the worker’s skill rather than replace it.
In short, machines handle heavy lifting, precision, or routine spraying (keeping farmers out of harm’s way), but people still do the planning, mixing, and fine decision-making (like spotting a disease) in this role.

AI in the real world
Whether farms rush to use AI tools depends on many factors. Big farms with steep plots or labor shortages are quicker to invest. In France, for example, lawmakers just allowed drones to spray “low-risk” pesticides on steep vineyards because drones are faster and safer than manual spraying [6].
Saving labor is a big reason: many growers face worker woe, so even expensive robots become attractive if they cut down hard, costly work [5] [7]. Indeed, industry studies say precision spray systems can save chemicals and make crop care more efficient [7] [6].
On the flip side, new gear is expensive and complex. Small farmers may hesitate if the upfront cost or training is high [5] [7]. and many want proof that machines do as good a job as people. Social factors matter too: people worry about losing work or having to learn new skills.
Regulations also play a role – some countries now safely allow agricultural drones under strict rules [6]. In the U.S., job projections remain steady [3], reflecting that many growers expect people to keep doing this work.
Overall, AI and robots will likely continue augmenting this career – taking over the toughest or most precise parts (like large-area spraying) and helping growers save time and chemicals. But human skills (judgment, careful mixing, disease recognition, and safe operation) will still be valuable. The future is more about people working with machines than being wholly replaced by them [7] [1].

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Median Wage
$45,200
Jobs (2024)
29,600
Growth (2024-34)
+3.8%
Annual Openings
4,100
Education
High school diploma or equivalent
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2024-2034
AI-generated estimates of task resilience over the next 3 years
Provide driving instructions to truck drivers to ensure complete coverage of designated areas, using hand and horn signals.
Identify lawn or plant diseases to determine the appropriate course of treatment.
Lift, push, and swing nozzles, hoses, and tubes to direct spray over designated areas.
Plant grass with seed spreaders and operate straw blowers to cover seeded areas with mixtures of asphalt and straw.
Cover areas to specified depths with pesticides, applying knowledge of weather conditions, droplet sizes, elevation-to-distance ratios, and obstructions.
Clean or service machinery to ensure operating efficiency, using water, gasoline, lubricants, or hand tools.
Connect hoses and nozzles selected according to terrain, distribution pattern requirements, types of infestations, and velocities.
Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.

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