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 13-1021.00
Purchase farm products either for further processing or resale. Includes tree farm contractors, grain brokers and market operators, grain buyers, and tobacco buyers. May negotiate contracts.
Also called: Buyer · Grain Buyer · Grain Merchandiser · Purchasing Agent · Grain Origination Specialist · Tobacco Buyer · Agriculture Industry Coordinator · Agriculture Industry Specialist · Buying Agent · Cattle Broker · Cattle Buyer · Cattle Dealer
Job family: Business and Financial Operations Occupations
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-13-1021-00/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.
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 |
|---|---|---|---|
| Overall AI exposure (Felten et al.) Moderate | 66th | 0.8 | |
| LLM task exposure, γ (OpenAI / Eloundou) High | 95th | 1.0 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.1), with simple added tooling (β 0.5), and including AI-powered software (γ 1.0). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.
Most of this job's tasks can be done remotely (Dingel–Neiman), which tends to track with higher digital and AI exposure.
A pre-LLM (2013) estimate of how automatable this job is by computerization and robotics. Shown for historical context only — it is not part of any current AI ranking.
Frey–Osborne probability 0.9 · 74th percentile among occupations · High
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.
| Examine or test crops or products to estimate their value, determine their grade, or locate any evidence of disease or insect damage. | 0.4% | |
| Advise farm groups or growers on land preparation or livestock care techniques that will maximize the quantity and quality of production. | 0.2% |
The ILO's 2025 global study scores generative-AI exposure on the international ISCO-08 occupation system, not US SOC. Bridged through the published (and approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 crosswalk, this US occupation corresponds to the international occupation below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Buyers · 3323 | 39% | Minimal |
Read the whole six-band gradient on the GenAI exposure gradient page. The crosswalk is approximate: a US occupation can map to several international ones, and the ILO scores describe the international occupation, not this exact US role.
All 12 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 Expression | 4.0 | |
| Oral Comprehension | 3.6 | |
| Written Comprehension | 3.6 | |
| Deductive Reasoning | 3.6 | |
| Speech Clarity | 3.6 | |
| Problem Sensitivity | 3.4 | |
| Inductive Reasoning | 3.4 | |
| Near Vision | 3.4 | |
| Speech Recognition | 3.4 | |
| Written Expression | 3.3 | |
| Information Ordering | 3.1 | |
| Mathematical Reasoning | 3.1 | |
| Number Facility | 3.1 |
| Speaking | 3.9 | |
| Critical Thinking | 3.9 | |
| Active Listening | 3.8 | |
| Reading Comprehension | 3.4 | |
| Writing | 3.1 | |
| Active Learning | 3.1 | |
| Monitoring | 3.1 | |
| Mathematics | 3.0 |
| Persuasion | 3.4 | |
| Negotiation | 3.4 | |
| Judgment and Decision Making | 3.4 | |
| Complex Problem Solving | 3.3 | |
| Social Perceptiveness | 3.1 | |
| Coordination | 3.1 | |
| Time Management | 3.1 |
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
Showing the top 40 of 43.
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 . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Share of people in this occupation at each level of education.
| Bachelor's Degree | 76.8% | |
| Associate's Degree (or other 2-year degree) | 8.3% | |
| High School Diploma | 7.6% | |
| Some College Courses | 7.3% |
The interests and personal qualities O*NET associates with people who do this work.
| Enterprising | 4.9 | |
| Conventional | 4.8 | |
| Realistic | 4.6 |
| Agriculture | 4.5 | |
| Management/Administration | 3.8 | |
| Accounting | 3.6 | |
| Business Initiatives | 3.3 | |
| Office Work | 3.2 | |
| Sales | 2.8 | |
| Finance | 2.8 | |
| Transportation/Machine Operation | 2.1 | |
| Law | 2.1 |
| Dependability | 3.0 | |
| Attention to Detail | 2.2 | |
| Integrity | 2.0 | |
| Self-Confidence | 1.9 |
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 Buyers and Purchasing Agents, Farm Products — 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.
On the global GenAI exposure gradient this work sits around the 76th percentile of 427 international occupations.
Buyers and Purchasing Agents, Farm Products sit at the 83rd percentile of AI task overlap among U.S. occupations
Buyers and Purchasing Agents, Farm Products sit at the 83rd percentile of AI task overlap among U.S. occupations • Buyers and Purchasing Agents, Farm Products rank in the 83rd percentile (High 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) Source: Singulariki — "Buyers and Purchasing Agents, Farm Products". https://singulariki.com/roles/role-13-1021-00 Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.
AssetsShare imageMethodology & sourcesPress & newsroomThe newsroom
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. "Buyers and Purchasing Agents, Farm Products." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-13-1021-00
Singulariki. (2026). Buyers and Purchasing Agents, Farm Products. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-13-1021-00
@misc{singulariki-role-13-1021-00,
title = {Buyers and Purchasing Agents, Farm Products},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
url = {https://singulariki.com/roles/role-13-1021-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.