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The AI Resilience Report helps you understand how AI is likely to impact your current or future career. Drawing on data from over 1,500 occupations, it provides a clear snapshot to support informed career decisions.
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Somewhat Resilient
Last Update: 5/19/2026
Your role’s AI Resilience Score is
48.3%
Median Score
Meaningful human contribution
Measures the parts of the occupation that still require a human touch. This score averages data from up to four AI exposure datasets, focusing on the role’s resilience against automation.
Med
Long-term employer demand
Predicts the health of the job market for this role through 2034. Using Bureau of Labor Statistics data, it balances projected annual job openings (60%) with overall employment growth (40%).
Med
Sustained economic opportunity
Measures future earning potential and career flexibility. This score is a blend of total projected labor income (67%) and the role’s inherent ability to adapt to economic and technological shifts (33%).
Med
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.
There are a reasonable number of sources for this result, but there is some disagreement between them.
Contributing sources
AI Resilience Report forPrecision Agriculture Technicians
Precision Agriculture Technicians are somewhat less resilient to AI impacts than most occupations, according to our analysis of 5 sources.
Precision Agriculture Technicians are labeled "Somewhat Resilient" because AI is genuinely reshaping how this job works — automating the data analysis and field guidance that used to require more hands-on time — but it's also creating a real demand for skilled people to install, calibrate, and troubleshoot all that new technology. The workflows are shifting in meaningful ways, moving away from manual field tasks and toward managing sensors, interpreting AI-generated recommendations, and keeping complex systems running, which means the job looks noticeably different than it did even five years ago.
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View analysisChat with CoachLatest newsMore career infoAnalysisChatNewsMoreThis role is somewhat resilient
Precision Agriculture Technicians are labeled "Somewhat Resilient" because AI is genuinely reshaping how this job works — automating the data analysis and field guidance that used to require more hands-on time — but it's also creating a real demand for skilled people to install, calibrate, and troubleshoot all that new technology. The workflows are shifting in meaningful ways, moving away from manual field tasks and toward managing sensors, interpreting AI-generated recommendations, and keeping complex systems running, which means the job looks noticeably different than it did even five years ago.
Read full analysisAnalysis of Current AI Resilience
Precision Ag Technician
Updated Quarterly • Last Update: 5/14/2026
How is AI changing Precision Ag Technician jobs?
The good news for anyone curious about this career is that AI is mostly augmenting precision agriculture technicians rather than replacing them. Tools like satellite imagery, AI-powered yield maps, autosteer GPS, and variable-rate sprayers already handle a lot of the data crunching and field guidance, freeing technicians to focus on installation, calibration, and decision-making. According to USDA's Economic Research Service, autosteering systems were used on 70% of large-scale crop farms in 2023, and yield monitors and soil maps on 68%, with adoption motivated by goals to "increase yields, save labor time, reduce purchased input costs" [1].
Generative AI is just beginning to enter the picture: Bushel's 2026 State of the Farm Report found that only 14% of farmers reported using AI tools, and among larger farms using AI, 50% used it for business or financial analysis while only 25% used it for yield prediction or agronomy [2]. Importantly, precision agriculture "modifies agricultural labor demand, shifting from manual work to technical and analytical tasks managing and maintaining sensors, robots and data platforms" [3] — meaning more humans, not fewer, are needed to keep the tech running.
Sources
How fast is AI adoption growing for Precision Ag Technician?
AI adoption is accelerating because the economic case is strong: a Deloitte study projected precision agriculture solutions could save farmers an estimated $40 billion to $100 billion in input costs by 2030 [4], and rising labor costs make automation attractive. But adoption is also being slowed by a workforce bottleneck. University of Illinois researchers found that higher precision agriculture use at the state level is associated with greater technician employment per farm and higher wages, suggesting "a farm service technician shortage is real" and that "efforts to develop a technician and service ecosystem may be needed to sustain existing precision agriculture use" [5].
For high schoolers, the takeaway is hopeful: the hands-on skills of installing, calibrating, troubleshooting, and interpreting AI-generated recommendations — exactly the lower-automation tasks in this role — are the very skills the industry can't find enough people to fill.
Sources
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More Career Info
Career: Precision Agriculture Technicians
They use technology to help farmers grow crops more efficiently by collecting data on soil, weather, and plant health to make better farming decisions.
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Employment & Wage Data
Median Wage
$46,790
Jobs (2024)
18,600
Growth (2024-34)
+4.3%
Annual Openings
2,900
Education
Associate's degree
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2024-2034
Task-Level AI Resilience Scores
AI-generated estimates of task resilience over the next 3 years
1
Install, calibrate, or maintain sensors, mechanical controls, GPS-based vehicle guidance systems, or computer settings.
2
Provide advice on the development or application of better boomspray technology to limit the overapplication of chemicals and to reduce the migration of chemicals to areas other than the fields being ...
3
Participate in efforts to advance precision agriculture technology, such as developing advanced weed identification or automated spot spraying systems.
4
Program farm equipment, such as variable-rate planting equipment or pesticide sprayers, based on input from crop scouting and analysis of field condition variability.
5
Prepare reports summarizing field productivity and profitability in graphical or tabular form.
6
Recommend best crop varieties or seeding rates for specific field areas, based on analysis of geospatial data.
7
Draw or read maps, such as soil, contour, or plat maps.
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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