Skills it runs on
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Occupation · SOC 19-4012.00
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.
Also called: Agricultural Research Technician (Agricultural Research Tech) · Agricultural Technician (Agricultural Tech) · Agriculture Assistant · Seed Analyst · Agricultural Research Technologist · Agronomy Research Technician (Agronomy Research Tech) · Field Assistant · Insect Research Technician (Insect Research Tech) · Lab Tech (Laboratory Technician) · Acidity Tester · Agricultural Assistant · Agricultural Equipment Technician
Job family: Life, Physical, and Social Science Occupations
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-19-4012-00/context.md directly.
A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Independent published positions, read together — not a forecast.
40th-percentile task overlap — yet about 2,900 openings a year (+4.3% projected, BLS) . What exposure means →
What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.
Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.
| Measure | Rank vs all occupations | Percentile | Score |
|---|---|---|---|
| LLM task exposure, γ (OpenAI / Eloundou) Moderate | 41st | 0.4 | |
| AI assistant applicability (Microsoft) Moderate | 42nd | 0.1 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.2), with simple added tooling (β 0.3), and including AI-powered software (γ 0.4). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.
Among measured AI assistant conversations mapped to this occupation (Anthropic Economic Index, 2026-01-15), these task types came up most. These are shares of observed AI conversations — not shares of the job, of worker time, or of what could be automated.
| Respond to general inquiries or requests from the public. | 2.0% | |
| Prepare data summaries, reports, or analyses that include results, charts, or graphs to document research findings and results. | 1.5% | |
| Prepare or present agricultural demonstrations. | 0.3% |
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | About average · +4.3% by 2034 |
| Projected annual openings | 2,900 |
| Employment 2024 → 2034 | 18,600 → 19,400 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
All 26 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
O*NET importance rating, from 1 (not important) to 5 (extremely important).
| Oral Comprehension | 3.8 | |
| Oral Expression | 3.8 | |
| Problem Sensitivity | 3.8 | |
| Near Vision | 3.6 | |
| Written Comprehension | 3.5 | |
| Written Expression | 3.4 | |
| Deductive Reasoning | 3.4 | |
| Inductive Reasoning | 3.3 | |
| Information Ordering | 3.3 | |
| Category Flexibility | 3.1 | |
| Arm-Hand Steadiness | 3.1 | |
| Visual Color Discrimination | 3.1 | |
| Fluency of Ideas | 3.0 | |
| Originality | 3.0 | |
| Mathematical Reasoning | 3.0 | |
| Number Facility | 3.0 | |
| Flexibility of Closure | 3.0 | |
| Perceptual Speed | 3.0 | |
| Selective Attention | 3.0 | |
| Control Precision | 3.0 | |
| Far Vision | 3.0 | |
| Speech Recognition | 3.0 |
| Food Production | 3.6 | |
| Biology | 3.5 | |
| Chemistry | 3.4 | |
| Mechanical | 3.4 | |
| Mathematics | 3.1 | |
| Administration and Management | 3.0 |
| Reading Comprehension | 3.4 | |
| Active Listening | 3.3 | |
| Critical Thinking | 3.3 | |
| Writing | 3.1 | |
| Active Learning | 3.1 | |
| Monitoring | 3.1 | |
| Speaking | 3.0 |
| Judgment and Decision Making | 3.1 | |
| Coordination | 3.0 | |
| Instructing | 3.0 | |
| Operations Monitoring | 3.0 | |
| Time Management | 3.0 |
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
| Example | Category | |
|---|---|---|
| Microsoft Excel | Spreadsheet software | Hot technology In demand |
| Microsoft Office software | Office suite software | Hot technology In demand |
| Microsoft Access | Data base user interface and query software | Hot technology |
| Microsoft Outlook | Electronic mail software | Hot technology |
| Microsoft PowerPoint | Presentation software | Hot technology |
| Microsoft Word | Word processing software | Hot technology |
| SAP software | Enterprise resource planning ERP software | Hot technology |
| Email software | Electronic mail software | |
| Geographic information system GIS systems | Geographic information system | |
| Global positioning system GPS software | Mobile location based services software | |
| Statistical software | Analytical or scientific software | |
| Web browser software | Internet browser software |
How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.
What to study: Agriculture, Agriculture Operations, and Related Sciences , Biological and Biomedical Sciences . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Share of people in this occupation at each level of education.
| High School Diploma | 41.3% | |
| Bachelor's Degree | 18.2% | |
| Associate's Degree (or other 2-year degree) | 13.2% | |
| Doctoral Degree | 7.2% | |
| Post-Baccalaureate Certificate | 6.0% | |
| Some College Courses | 5.5% | |
| Master's Degree | 5.5% | |
| Less than a High School Diploma | 3.2% |
The interests and personal qualities O*NET associates with people who do this work.
| Realistic | 6.8 | |
| Investigative | 4.6 | |
| Conventional | 4.3 |
| Agriculture | 5.8 | |
| Physical/Manual Labor | 5.6 | |
| Life Science | 5.1 | |
| Transportation/Machine Operation | 5.0 | |
| Nature/Outdoors | 5.0 | |
| Mechanics/Electronics | 3.4 | |
| Animal Service | 2.5 | |
| Engineering | 2.5 | |
| Physical Science | 2.4 | |
| Medical Science | 2.4 | |
| Mathematics/Statistics | 2.3 |
| Dependability | 2.3 | |
| Attention to Detail | 2.0 |
U.S. · annual wages (BLS OEWS)
| 10th percentile | $32,860 |
| 25th percentile | $38,480 |
| Median (50th) | $46,790 |
| 75th percentile | $59,370 |
| 90th percentile | $69,010 |
| People employed | 14,340 |
Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.
| Industry | Workers | National median pay |
|---|---|---|
| Professional, Scientific, and Technical Services · Sector | 4,990 | $45,070 |
| Educational Services · Sector | 3,950 | $50,650 |
| Wholesale Trade · Sector | 1,450 | $45,890 |
| Testing Laboratories and Services · National industry | 1,300 | $42,690 |
| Agriculture, Forestry, Fishing and Hunting · Sector | 1,080 | $40,420 |
| Manufacturing · Sector | 850 | $45,810 |
| Management of Companies and Enterprises · Sector | 420 | $46,260 |
| Retail Trade · Sector | 270 | $43,500 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 110 | $44,900 |
| Other Services (except Public Administration) · Sector | 100 | $37,520 |
| Temporary Help Services · National industry | 60 | $43,480 |
| Arts, Entertainment, and Recreation · Sector | 60 | $36,450 |
Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).
| Industry | Concentration | Workers |
|---|---|---|
| Testing Laboratories and Services · National industry | 82.03× | 1,300 |
| Agriculture, Forestry, Fishing and Hunting · Sector | 27.43× | 1,080 |
| Professional, Scientific, and Technical Services · Sector | 4.98× | 4,990 |
| Educational Services · Sector | 3.11× | 3,950 |
| Wholesale Trade · Sector | 2.58× | 1,450 |
| Management of Companies and Enterprises · Sector | 1.61× | 420 |
| Manufacturing · Sector | 0.72× | 850 |
| Other Services (except Public Administration) · Sector | 0.24× | 100 |
Part of the Agriculture career cluster.
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
Options the data surfaces for Agricultural Technicians — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Capabilities this work builds that are used across many other occupations.
Occupations O*NET rates as related — the nearby moves on the map.
How people typically prepare for this work.
See where this work sits in the bigger picture.
Agricultural Technicians show 40th-percentile AI task overlap — and about 2,900 annual U.S. openings
Agricultural Technicians show 40th-percentile AI task overlap — and about 2,900 annual U.S. openings • Agricultural Technicians rank in the 40th percentile (Moderate band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE) • The occupation is projected to see about 2,900 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34) • BLS projects employment to be about average (+4.3%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $46,790, across about 14,340 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "Agricultural Technicians". https://singulariki.com/roles/role-19-4012-00 Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.
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Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.
Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.
Data compiled June 2, 2026. Figures are estimates, not advice.
Singulariki. "Agricultural Technicians." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026. https://singulariki.com/roles/role-19-4012-00
Singulariki. (2026). Agricultural Technicians. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-19-4012-00
@misc{singulariki-role-19-4012-00,
title = {Agricultural Technicians},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026},
url = {https://singulariki.com/roles/role-19-4012-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.