Agricultural Technicians
SOC: 19-4012.00 · Job Zone: 3
Key Takeaways
- ●AI Impact Score: 48/100 — Partial Automation Likely. Partial automation is likely for key tasks in this occupation.
- ●14K workers currently employed.
- ●Mean annual wage: $46,790.
- ●5 of 15 key tasks can already be performed by AI tools today.
What Agricultural Technicians Do
Work with agricultural scientists in plant, fiber, and animal research, or assist with animal breeding and nutrition. Set up or maintain laboratory equipment and collect samples from crops or animals. Prepare specimens or record data to assist scientists in biology or related life science experiments. Conduct tests and experiments to improve yield and quality of crops or to increase the resistance of plants and animals to disease or insects.
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AI Impact Analysis
Agricultural Technicians represent a specialized workforce of 14,340 professionals earning a mean annual wage of $46,790, supporting critical agricultural research and production operations. This occupation sits at the intersection of traditional farming and scientific research, making it particularly vulnerable to AI-driven automation as precision agriculture technologies mature.
AI is already automating several core tasks performed by Agricultural Technicians. Data recording and analysis tasks are being handled by platforms like Microsoft Copilot integrated with Excel, while report generation is increasingly automated through GPT-4 and Claude for creating data summaries and research documentation. Laboratory testing protocols are being standardized through workflow automation tools like UiPath, and sample preparation tracking is managed by AI-enhanced LIMS (Laboratory Information Management Systems). Pest identification and crop monitoring are being revolutionized by computer vision platforms like PlantNet and agricultural AI tools such as Taranis and Blue River Technology.
Critical tasks remain human-essential due to their physical nature and complex decision-making requirements. Operating farm machinery, preparing land through plowing and discing, and hands-on crop production activities like pruning and harvesting require human dexterity and situational awareness. Equipment maintenance and repair demand troubleshooting skills that combine technical knowledge with physical manipulation. Most importantly, the coordination between field operations and laboratory work requires human judgment to adapt protocols based on real-time conditions.
The automation timeline shows immediate impact in data management and analysis (already happening), followed by enhanced laboratory automation within 1-3 years as AI-powered equipment becomes standard. The 3-5 year horizon will see significant automation in monitoring and basic testing procedures, while physical field operations and complex problem-solving will remain human-dominated beyond 5 years. This trajectory aligns with our 48/100 AI Impact Score, indicating substantial task automation without complete role replacement.
Major agricultural companies are actively deploying AI solutions. John Deere has integrated AI into farming equipment for autonomous operation guidance, while companies like Indigo Agriculture use machine learning for crop optimization. Research institutions are implementing AI-powered laboratory management systems, and precision agriculture firms like Climate Corporation (owned by Bayer) are automating data analysis and recommendation generation that traditionally required technician input.
Task-by-Task AI Analysis
| Task | AI Status |
|---|---|
Record data pertaining to experimentation, research, or animal care. AI can automatically capture, organize, and standardize data entry from various sensors and inputs. | AI Can Do This Now |
Prepare data summaries, reports, or analyses that include results, charts, or graphs to document research findings and results. AI excels at generating formatted reports and visualizations from structured datasets. | AI Can Do This Now |
Perform laboratory or field testing, using spectrometers, nitrogen determination apparatus, air samplers, centrifuges, or potential hydrogen (pH) meters to perform tests. AI can automate test protocols and data collection, but equipment setup and troubleshooting require human oversight. | AI Assists 1-2 years |
Prepare laboratory samples for analysis, following proper protocols to ensure that they will be stored, prepared, and disposed of efficiently and effectively. AI can optimize protocols and track samples, but physical preparation requires human handling. | AI Assists 1-2 years |
Examine animals or crop specimens to determine the presence of diseases or other problems. Computer vision can identify many diseases, but complex diagnoses still need human expertise. | AI Assists 1-2 years |
Conduct studies of nitrogen or alternative fertilizer application methods, quantities, or timing to ensure satisfaction of crop needs and minimization of leaching, runoff, or denitrification. AI models can optimize fertilizer application based on soil data and weather patterns. | AI Can Do This Now |
Perform tests on seeds to evaluate seed viability. AI can assess seed quality through image analysis and standardized testing protocols. | AI Can Do This 1-2 years |
Measure or weigh ingredients used in laboratory testing. Robotic systems can precisely measure and dispense laboratory materials. | AI Can Do This 3-5 years |
Collect animal or crop samples. Sample collection requires human judgment for location selection and proper handling techniques. | Human Essential 5+ years |
Set up laboratory or field equipment as required for site testing. Equipment setup requires physical manipulation and adaptation to varying field conditions. | Human Essential 5+ years |
Supervise pest or weed control operations, including locating and identifying pests or weeds, selecting chemicals and application methods, or scheduling application. AI can identify pests and recommend treatments, but supervision and application decisions need human oversight. | AI Assists 1-2 years |
Operate farm machinery, including tractors, plows, mowers, combines, balers, sprayers, earthmoving equipment, or trucks. While AI assists with guidance, human operators are still required for safety and complex maneuvering. | Human Essential 5+ years |
Prepare land for cultivated crops, orchards, or vineyards by plowing, discing, leveling, or contouring. Land preparation requires human assessment of soil conditions and terrain-specific decision making. | Human Essential 5+ years |
Maintain or repair agricultural facilities, equipment, or tools to ensure operational readiness, safety, and cleanliness. Maintenance and repair require hands-on troubleshooting and mechanical skills that AI cannot replicate. | Human Essential 5+ years |
Perform crop production duties, such as tilling, hoeing, pruning, weeding, or harvesting crops. These tasks require fine motor skills and real-time adaptation to plant conditions. | Human Essential 5+ years |
AI Tools Disrupting Agricultural Technicians
Key Skills
Key Tasks
- •Prepare land for cultivated crops, orchards, or vineyards by plowing, discing, leveling, or contouring.
- •Operate farm machinery, including tractors, plows, mowers, combines, balers, sprayers, earthmoving equipment, or trucks.
- •Record data pertaining to experimentation, research, or animal care.
- •Maintain or repair agricultural facilities, equipment, or tools to ensure operational readiness, safety, and cleanliness.
- •Conduct studies of nitrogen or alternative fertilizer application methods, quantities, or timing to ensure satisfaction of crop needs and minimization of leaching, runoff, or denitrification.
- •Prepare laboratory samples for analysis, following proper protocols to ensure that they will be stored, prepared, and disposed of efficiently and effectively.
- •Measure or weigh ingredients used in laboratory testing.
- •Perform crop production duties, such as tilling, hoeing, pruning, weeding, or harvesting crops.
- •Perform tests on seeds to evaluate seed viability.
- •Prepare data summaries, reports, or analyses that include results, charts, or graphs to document research findings and results.
- •Collect animal or crop samples.
- •Perform laboratory or field testing, using spectrometers, nitrogen determination apparatus, air samplers, centrifuges, or potential hydrogen (pH) meters to perform tests.
Technology Skills Used
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Salary Range
Career Transition Guidance
Agricultural Technicians facing AI disruption have strong transition pathways to related technical roles. The most natural progression is to Precision Agriculture Technicians (19-4012.01), which builds directly on existing skills while adding AI and sensor technology expertise. Biological Technicians (19-4021.00) offer similar laboratory and research skills with broader application beyond agriculture. For those with leadership experience, First-Line Supervisors of Farming, Fishing, and Forestry Workers (45-1011.00) leverages coordination and instructing skills that AI cannot replicate.
Key transferable skills include data recording, laboratory procedures, equipment operation, and critical thinking. To transition successfully, Agricultural Technicians should pursue additional training in data analytics, precision agriculture technologies, and AI system management. Professional certifications in GIS systems, statistical software, and agricultural engineering principles strengthen career prospects. The timeline for transition varies: moving to Precision Agriculture roles requires 6-12 months of technology training, while advancing to supervisory positions may take 2-3 years of leadership development.
For those seeking higher-level roles, Agricultural Engineers (17-2021.00) and Food Scientists and Technologists (19-1012.00) represent longer-term career goals requiring additional formal education. However, the practical experience in crop production, laboratory procedures, and equipment operation provides a strong foundation for these advanced positions. The key is to begin skill development now, as the most successful transitions will occur for those who proactively adapt rather than wait for displacement.
Related Occupations
Frequently Asked Questions
Will AI replace Agricultural Technicians?
AI will not completely replace Agricultural Technicians but will significantly transform the role. With our 48/100 AI Impact Score, approximately half of current tasks will be automated within 5-10 years, particularly data management and laboratory testing procedures. The 14,340 workers in this field will need to adapt to more supervisory and complex problem-solving responsibilities.
What AI tools are used in Agricultural Technicians roles?
Current AI tools include Microsoft Copilot for data analysis, GPT-4 for report generation, UiPath for laboratory workflow automation, Climate FieldView for precision agriculture, PlantNet for plant identification, and Taranis for pest monitoring. Traditional tools like Microsoft Excel and SAP software are being enhanced with AI capabilities.
What is the salary outlook for Agricultural Technicians with AI?
The current mean annual wage of $46,790 may increase for technicians who develop AI management skills, as they'll oversee more automated systems and focus on higher-value analytical work. However, positions focused solely on routine data collection and basic testing may see wage pressure as these tasks become automated.
What skills should Agricultural Technicians develop for the AI era?
Focus on skills that AI cannot easily replicate: Critical Thinking (3.25/5 importance), Judgment and Decision Making (3.12/5), and Coordination (3/5). Develop expertise in AI tool management, complex problem-solving, and equipment maintenance. Human skills like Active Listening and Instructing become more valuable as technicians supervise automated systems.
How many Agricultural Technicians jobs are there in the US?
There are currently 14,340 Agricultural Technicians employed in the US. While no projected change data is available, the role will likely evolve rather than disappear, with job responsibilities shifting toward AI system oversight and complex analytical tasks that require human judgment.