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Automation Risk Analysis

Will “Field Sales Agronomist” be Automated?

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AI Exposure Risk

57%

“Field Sales Agronomist” will maybe be replaced by AI.

Based on the cognitive demands, communication requirements, and logical reasoning intrinsic to this occupation according to O*NET data, we project a 57% probability of disruption by generative AI and Large Language Models.

Automation & Robot Risk

47%

“Field Sales Agronomist” will probably not be replaced by robots.

Evaluating the physical dexterity, repetitive motion tasks, and manual labor associated with this role, our analysis indicates a 47% likelihood of substitution by advanced robotics systems.

Personal & Financial Insights

Every occupation has a unique profile. For Precision Agriculture Technicians, the Bureau of Labor Statistics and O*NET classify the day-to-day work broadly as: Apply geospatial technologies, including geographic information systems (GIS) and Global Positioning System (GPS), to agricultural production or management activities, such as pest scouting, site-specific pesticide application, yield mapping, or variable-rate irrigation. May use computers to develop or analyze maps or remote sensing images to compare physical topography with data on soils, fertilizer, pests, or weather.

Job Title & Hierarchy Code (SOC) Precision Agriculture Technicians #19-4012.01
ℹ️

Data is based on the reference occupation: “Precision Agriculture Technicians”

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Core Skills & Abilities

  • Document and maintain records of precision agriculture information.

  • Install, calibrate, or maintain sensors, mechanical controls, GPS-based vehicle guidance systems, or computer settings.

  • Prepare reports in graphical or tabular form, summarizing field productivity or profitability.

  • Participate in efforts to advance precision agriculture technology, such as developing advanced weed identification or automated spot spraying systems.

  • Create, layer, and analyze maps showing precision agricultural data, such as crop yields, soil characteristics, input applications, terrain, drainage patterns, or field management history.

  • Collect information about soil or field attributes, yield data, or field boundaries, using field data recorders and basic geographic information systems (GIS).

  • Recommend best crop varieties or seeding rates for specific field areas, based on analysis of geospatial data.

  • Compare crop yield maps with maps of soil test data, chemical application patterns, or other information to develop site-specific crop management plans.

  • Advise farmers on upgrading Global Positioning System (GPS) equipment to take advantage of newly installed advanced satellite technology.

  • Analyze geospatial data to determine agricultural implications of factors such as soil quality, terrain, field productivity, fertilizers, or weather conditions.

  • Program farm equipment, such as variable-rate planting equipment or pesticide sprayers, based on input from crop scouting and analysis of field condition variability.

  • Contact equipment manufacturers for technical assistance, as needed.

  • Apply precision agriculture information to specifically reduce the negative environmental impacts of farming practices.

  • Identify spatial coordinates, using remote sensing and Global Positioning System (GPS) data.

  • 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.

  • Draw or read maps, such as soil, contour, or plat maps.

  • 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.

  • 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.

  • Analyze remote sensing imagery to identify relationships between soil quality, crop canopy densities, light reflectance, and weather history.

  • Analyze data from harvester monitors to develop yield maps.

  • Identify areas in need of pesticide treatment by analyzing geospatial data to determine insect movement and damage patterns.

  • Divide agricultural fields into georeferenced zones, based on soil characteristics and production potentials.

Technologies & Software

  • Geographic information system GIS systems
  • Microsoft PowerPoint
  • Microsoft Access
  • Farm Works Site Pro
  • Qwen (Alibaba)
  • DeepSeek
  • Claude (Anthropic)
  • ESRI ArcGIS software
  • ChatGPT (OpenAI)
  • John Deere Apex Farm Management
  • Llama (Meta)
  • Microsoft Outlook
  • Microsoft Windows
  • Microsoft Excel
  • Novariant AutoFarm AF Viewer
  • Trimble AgGPS MultiPlane
  • Ag Leader Technology SMS Advanced
  • Gemini for Workspace
  • Gemini (Google)
  • Microsoft Office software
  • Elicit
  • NotebookLM (Google)
  • Semantic Scholar AI
  • ESRI ArcPad
  • Consensus
  • Kimi (Moonshot AI)
  • Grok (xAI)
  • Mistral AI (chat/models)
  • Mistral (Mistral AI)
  • Scite AI
  • MapShots EASi Suite
  • ESRI ArcView
  • Global positioning system GPS software
  • AGCO GTA Software Suite
  • GeoAgro GIS
  • Microsoft Word
  • SST Development Group SSToolbox
  • Web browser software
  • Nova (Amazon)
  • Trimble AgGPS EZ-Map
  • Perplexity AI
  • Yield monitor systems
  • Global positioning system GPS receivers
  • Fertilizer spreading equipment
  • Tractor mounted soil probes
  • Air clutches
  • Moisture monitors
  • Sprayer application equipment
  • Personal computers
  • Lightbar guidance systems
  • Desktop computers
  • Laptop computers
  • Autosteering systems
  • Automatic land leveling systems
  • Variable rate applicators
  • Automatic boom control systems
  • Soil samplers
  • Seed drills
  • Field personal computers PC
  • Soil electrical conductivity measurement devices