AI exposure by occupation, O*NET 19-4012.01
Will AI replace Precision Agriculture Technicians?
Precision Agriculture Technicians: AI can already handle 14 of 22 tasks; the work mostly needs a frontier-tier model.
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Every task, scored
The 22 tasks O*NET 30.3 lists for Precision Agriculture Technicians, from most to least exposed. 14 reach 60 or more, the level at which AI already handles a task.
| Task | AI exposure | Evidence | Model tier |
|---|---|---|---|
| Analyze data from harvester monitors to develop yield maps. | Estimated | Standard | |
| Collect information about soil or field attributes, yield data, or field boundaries, using field data recorders and basic geographic information systems (GIS). | Estimated | Efficient | |
| Divide agricultural fields into georeferenced zones, based on soil characteristics and production potentials. | Estimated | Standard | |
| Create, layer, and analyze maps showing precision agricultural data, such as crop yields, soil characteristics, input applications, terrain, drainage patterns, or field management history. | Estimated | Frontier | |
| Analyze geospatial data to determine agricultural implications of factors such as soil quality, terrain, field productivity, fertilizers, or weather conditions. | Estimated | Standard | |
| Apply precision agriculture information to specifically reduce the negative environmental impacts of farming practices. | Estimated | Frontier | |
| Demonstrate the applications of geospatial technology, such as Global Positioning System (GPS), geographic information systems (GIS), automatic tractor guidance systems, variable rate chemical input applicators, surveying equipment, or computer mapping software. | Estimated | Standard | |
| Draw or read maps, such as soil, contour, or plat maps. | Estimated | Frontier | |
| Prepare reports in graphical or tabular form, summarizing field productivity or profitability. | Estimated | Efficient | |
| Analyze remote sensing imagery to identify relationships between soil quality, crop canopy densities, light reflectance, and weather history. | Estimated | Efficient | |
| Contact equipment manufacturers for technical assistance, as needed. | Estimated | Standard | |
| Identify areas in need of pesticide treatment by analyzing geospatial data to determine insect movement and damage patterns. | Estimated | Standard | |
| Recommend best crop varieties or seeding rates for specific field areas, based on analysis of geospatial data. | Estimated | Frontier | |
| Advise farmers on upgrading Global Positioning System (GPS) equipment to take advantage of newly installed advanced satellite technology. | Estimated | Frontier | |
| Use geospatial technology to develop soil sampling grids or identify sampling sites for testing characteristics such as nitrogen, phosphorus, or potassium content, pH, or micronutrients. | Estimated | Standard | |
| Compare crop yield maps with maps of soil test data, chemical application patterns, or other information to develop site-specific crop management plans. | Estimated | Efficient | |
| Identify spatial coordinates, using remote sensing and Global Positioning System (GPS) data. | Estimated | Standard | |
| Program farm equipment, such as variable-rate planting equipment or pesticide sprayers, based on input from crop scouting and analysis of field condition variability. | Estimated | Efficient | |
| Provide advice on the development or application of better boom-spray technology to limit the overapplication of chemicals and to reduce the migration of chemicals beyond the fields being treated. | Estimated | Frontier | |
| Participate in efforts to advance precision agriculture technology, such as developing advanced weed identification or automated spot spraying systems. | Estimated | Frontier | |
| Document and maintain records of precision agriculture information. | Estimated | Efficient | |
| Install, calibrate, or maintain sensors, mechanical controls, GPS-based vehicle guidance systems, or computer settings. | Estimated | Efficient |
Observed: scored from AI use recorded in the Anthropic Economic Index (June 2026 release), 0 of 22 tasks. Estimated: scored from the task's O*NET 30.3 work activity, 22 of 22. Importance is O*NET's 1 to 5 rating of how central the task is. Model tier is the lowest tier that can do the task under the published rubric; "No tier" marks hands-on work.
The model tier this role needs
A frontier-tier model or lower covers 100% of the role's importance-weighted task work. 100% of the work is something AI can address at some tier.
Efficient, standard and frontier tiers come from the JobRoute model tier reference. The recommended tier is the lowest one that covers 80% of the work AI can address. How the method works.
Wages, employment and outlook
- US employment
- 15,130
- Median annual wage
- $49,630
- Middle half of earners
- $40,950 to $63,630
- Projected change, 2024 to 2034
- +4.3%
Employment and wages: BLS Occupational Employment and Wage Statistics, May 2025, national. Projection: BLS Employment Projections 2024 to 2034. BLS publishes these figures by SOC code, so O*NET occupations that share a SOC code show the same figures.
Adjacent roles
The occupations that reuse the most of this role's skills, with the usual time to move. These are the first places to look when you plan to redeploy or retrain people in this role.
- Agricultural Technicians 79% skill overlap, about 8 months to move Exposure65
- Geographic Information Systems Technologists and Technicians 69% skill overlap, about 11 months to move Exposure63
- Agricultural Engineers 67% skill overlap, about 12 months to move Exposure56
- Remote Sensing Technicians 66% skill overlap, about 12 months to move Exposure58
- Surveying and Mapping Technicians 66% skill overlap, about 12 months to move Exposure70
Skill overlap and transition time from the JobRoute role adjacency graph on O*NET 30.3 skills.
Questions about Precision Agriculture Technicians and AI
Will AI replace Precision Agriculture Technicians?
AI already handles 14 of the 22 tasks O*NET lists for this occupation, at a task exposure of 60 or more, and the role's importance-weighted exposure is 62 out of 100. JobRoute scores tasks, not whole jobs, so the score shows how much of the work changes rather than whether the job disappears. BLS projects employment to change by +4.3% from 2024 to 2034.
What is the AI exposure of Precision Agriculture Technicians?
62 out of 100 on JobRoute's task exposure measure, the importance-weighted average of the role's O*NET task scores. Higher means more of the work is AI-doable today. 0 of the 22 task scores are observed in the Anthropic Economic Index (June 2026 release), and the other 22 are estimated from each task's O*NET work activity.
Which Precision Agriculture Technicians tasks can AI already do?
The tasks with the highest exposure are: Analyze data from harvester monitors to develop yield maps; Collect information about soil or field attributes, yield data, or field boundaries, using field data recorders and basic geographic information systems (GIS); Divide agricultural fields into georeferenced zones, based on soil characteristics and production potentials. They are three of the 14 tasks that reach 60 or more.
What AI model tier does this role need?
A frontier-tier model or lower covers 100% of the role's importance-weighted task work. JobRoute assigns each task the lowest tier that can do it under a published rubric and recommends the lowest tier that covers 80% of the work AI can address.
How many people work as Precision Agriculture Technicians, and what do they earn?
15,130 people in the United States, with a median annual wage of $49,630 (BLS Occupational Employment and Wage Statistics, May 2025). BLS Employment Projections expect a change of +4.3% from 2024 to 2034.
How to cite
Data version 2026-11-02, JobRoute method v1.0.0. Download all occupations or this occupation as JSON. Methodology.
JobRoute (2026). AI exposure: Precision Agriculture Technicians. Data version 2026-11-02, method v1.0.0. Built on O*NET 30.3, BLS OEWS May 2025 and the Anthropic Economic Index (June 2026). CC BY 4.0. https://www.jobroute.ai/jobs/precision-agriculture-technicians
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