Agricultural Technicians

Record data pertaining to experimentation, research, or animal care.

AI: Fully automatable - Recording experimental or animal-care data is routine and can be fully automated through sensors, LIMS, and automated logging systems.

Prepare data summaries, reports, or analyses that include results, charts, or graphs to document research findings and results.

AI: Fully automatable - AI can fully generate data summaries, charts, and reports from provided datasets, automating routine analysis and visualization tasks.

Record environmental data from field samples of soil, air, water, or pests to monitor the effectiveness of integrated pest management (IPM) practices.

AI: Fully automatable - Sensor networks, automated field instruments and AI pipelines can routinely record and log environmental sample data for IPM monitoring with high reliability today.

Prepare land for cultivated crops, orchards, or vineyards by plowing, discing, leveling, or contouring.

AI: Fully automatable - Autonomous tractors and implements are commercially deployed and can perform plowing, discing, leveling, and contouring with limited human oversight in many settings.

Operate farm machinery, including tractors, plows, mowers, combines, balers, sprayers, earthmoving equipment, or trucks.

AI: Fully automatable - AI-driven/autonomous systems and teleoperation are capable of operating a wide range of farm machinery and vehicles, with humans mainly providing oversight for atypical conditions.

Perform laboratory or field testing, using spectrometers, nitrogen determination apparatus, air samplers, centrifuges, or potential hydrogen (pH) meters to perform tests.

AI: Fully automatable - Laboratory and field instruments are widely automated and AI can run standard tests and analyze results without routine human intervention.

Perform tests on seeds to evaluate seed viability.

AI: Fully automatable - Seed viability testing uses standardized protocols that can be automated with germination chambers, imaging, and AI-based analysis tools.

Respond to general inquiries or requests from the public.

AI: Fully automatable - Contemporary conversational AI systems can handle the majority of general public inquiries reliably and at scale with minimal human involvement in 2025.

Prepare culture media, following standard procedures.

AI: Fully automatable - Culture media preparation follows standardized procedures that liquid-handling robots and automation platforms can execute reliably.

Determine the germination rates of seeds planted in specified areas.

AI: Fully automatable - Computer vision combined with fixed or drone imaging and automated counting can reliably determine seed germination rates across specified areas in typical conditions by 2025.

Measure or weigh ingredients used in laboratory testing.

AI: Partial - AI can control automated lab robotics to measure or weigh ingredients in many standardized settings, but many contexts still require human handling or validation, so only partial automation is realistic by 2025.

Perform crop production duties, such as tilling, hoeing, pruning, weeding, or harvesting crops.

AI: Partial - Robotics and automation can perform specific production tasks (weeding, selective harvesting) but full-spectrum crop production duties across crops and environments are not yet fully automated.

Prepare laboratory samples for analysis, following proper protocols to ensure that they will be stored, prepared, and disposed of efficiently and effectively.

AI: Partial - AI and automation can standardize protocols and drive robotic sample-handling systems, but human oversight and manual steps (especially for complex or novel samples and safe disposal) remain necessary in 2025.

Set up laboratory or field equipment as required for site testing.

AI: Partial - Setting up lab or field equipment often requires dexterous physical work, context-specific judgment, and safety decisions that prevent full automation, although AI can assist with instructions and configuration.

Examine animals or crop specimens to determine the presence of diseases or other problems.

AI: Partial - AI vision and diagnostics can identify many crop and animal diseases from images and data, but tactile exams, ambiguous cases, and regulatory/diagnostic confirmations still require human experts.

Collect animal or crop samples.

AI: Partial - Drones and robotic samplers can collect many field samples, yet variability of contexts, animal handling, and complex sampling still require human intervention or oversight.

Supervise pest or weed control operations, including locating and identifying pests or weeds, selecting chemicals and application methods, or scheduling application.

AI: Partial - AI can locate/identify pests, recommend chemicals and optimize schedules, but full autonomous supervision and safe/legal application across diverse sites still needs human decision-making and compliance checks.

Supervise or train agricultural technicians or farm laborers.

AI: Partial - AI can provide training content, monitoring, and performance analytics, but leadership, nuanced personnel management, and on-the-job mentorship remain human responsibilities.

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: Partial - AI can design experiments, model nutrient dynamics, and analyze results, but conducting field trials, accounting for site-specific variability, and final agronomic judgement still require human-led implementation and interpretation.

Conduct insect or plant disease surveys.

AI: Partial - Automated scouting with drones and computer vision can perform large-scale surveys and detection, but full replacement of expert-led surveys is limited by detection gaps, ground-truthing needs, and complex habitats.

Maintain or repair agricultural facilities, equipment, or tools to ensure operational readiness, safety, and cleanliness.

AI: Partial - AI can assist with diagnostics and operate cleaning/inspection robots, but complex, ad hoc mechanical repairs and safety judgments still require human technicians.

Perform general nursery duties, such as propagating standard varieties of plant materials, collecting and germinating seeds, maintaining cuttings of plants, or controlling environmental conditions.

AI: Partial - Greenhouse environmental control and many propagation tasks are automated, but delicate cutting maintenance, nuanced propagation decisions, and nonstandard work still need human skill.

Devise cultural methods or environmental controls for plants for which guidelines are sketchy or nonexistent.

AI: Partial - Devising cultural methods for poorly documented plants requires creative experimentation, tacit knowledge, and iterative adaptation that AI can support but not fully replace.

Prepare or present agricultural demonstrations.

AI: Partial - AI can prepare content and deliver virtual or scripted demonstrations, but live, hands-on, locally adaptive agricultural demonstrations still require human presenters and logistics.

Transplant trees, vegetables, or horticultural plants.

AI: Partial - Robotic transplanters handle seedlings and uniform horticultural transplants well, but transplanting larger trees and irregular specimens remains largely manual.

Assess comparative soil erosion from various planting or tillage systems, such as conservation tillage with mulch or ridge till systems, no-till systems, or conventional tillage systems with or without moldboard plows.

AI: Partial - AI can analyze remote sensing, models, and proxy measurements to estimate comparative erosion, but fully replacing field measurements, long‑term monitoring, and expert interpretation is not yet consistent across all contexts.