Precision Agriculture Technicians
of tasks in the Precision Agriculture Technicians role are ones AI can already do, per AI experts.
From a Stanford study where AI experts and precision agriculture technicians workers rated each real task (O*NET). Not a guess from the job title.
Key statistics
Free to cite, with a link back to Automatable.
- AI can already do 29% of the 7 work tasks in the Precision Agriculture Technicians role, according to AI experts in the Stanford WORKBank study (O*NET SOC 19-4012.01).
- Workers in the Precision Agriculture Technicians role want about 71% of their tasks automated (Stanford WORKBank, 1,500 U.S. workers).
- 2 of 7 Precision Agriculture Technicians tasks are Automation Green Light, wanted by workers and do-able by AI, that is 29% of the role (Stanford WORKBank).
- The typical Precision Agriculture Technicians task scores 2.99/5 for worker desire to automate and 3.17/5 for AI capability today (Stanford WORKBank, 1-5 scale).
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What workers told Stanford
Of the 7 tasks studied for Precision Agriculture Technicians, 2 (29%) are in the Automation Green Light zone, AI can largely do them and workers want it. Across all tasks, workers want about 71% automated. The typical task scores 2.99/5 for worker desire and 3.17/5 for AI capability.
All 7 tasks, most-wanted first
Analyze remote sensing imagery to identify relationships between soil quality, crop canopy densities, light reflectance, and weather history.
R&D Opportunitywant 3.5 · AI 3.33Identify spatial coordinates, using remote sensing and Global Positioning System (GPS) data.
Green Lightwant 3.33 · AI 3.5Create, layer, and analyze maps showing precision agricultural data, such as crop yields, soil characteristics, input applications, terrain, drainage patterns, or field management history.
Green Lightwant 3 · AI 3.5Draw or read maps, such as soil, contour, or plat maps.
R&D Opportunitywant 3 · AI 3.33Program farm equipment, such as variable-rate planting equipment or pesticide sprayers, based on input from crop scouting and analysis of field condition variability.
R&D Opportunitywant 3 · AI 2.5Document and maintain records of precision agriculture information.
Low Prioritywant 2.86 · AI 3Analyze geospatial data to determine agricultural implications of factors such as soil quality, terrain, field productivity, fertilizers, or weather conditions.
Low Prioritywant 2.25 · AI 3
Related occupations
Other Life, Physical, and Social Science roles in the Stanford WORKBank study, closest AI-capability share first.
- Quality Control AnalystsAI can do 38% of tasks today · workers want 75% automated
- GeographersAI can do 50% of tasks today · workers want 25% automated
- Social Science Research AssistantsAI can do 80% of tasks today · workers want 80% automated
- Bioinformatics ScientistsAI can do 86% of tasks today · workers want 71% automated
Lower-automation alternatives
Less of these jobs is automatable today: AI experts rate a smaller share of their tasks as doable than the 29% for Precision Agriculture Technicians (Stanford WORKBank).