Meat, Poultry, and Fish Cutters and Trimmers
Production Occupations- O*NET-SOC code
- 51-3022.00
Use hands or hand tools to perform routine cutting and trimming of meat, poultry, and seafood.
- Data source: BLSPublished: 2026-08
Moderate· relative
LowFour relative bandsVery highGroup-level value
Scale, basis and source
Four relative bands (Low / Moderate / High / Very high)
831 detailed occupations in the BLS Employment Projections table. Assigned per National Employment Matrix (NEM) code, so occupations sharing a NEM code carry the same band
- Data source: AnthropicPublished: 2026-03
0.000
0.000Range of values carried here0.745Scale, basis and source
Observed exposure index, 0–1 as published
Mapped onto O*NET tasks
Published per SOC 2018 occupation; every O*NET occupation with the same SOC 2018 code carries this value
- Data source: ILOPublished: 2025
0.13
0.09Range of values carried here0.70Group-level value
Scale, basis and source
Generative AI exposure index, 0–1 as published
Published per ISCO-08 unit group. Linked to this occupation, wholly or in part, by applying U.S. Bureau of Labor Statistics crosswalks (ISCO-08 to 2010 SOC, 2010 SOC to 2018 SOC) as published
What kind of figure this source publishes
The BLS category is a relative rank, not an absolute level, and it is not a first-hand measurement: it groups an occupation's percentile ranks across several published studies into four bands. It is not an employment or wage forecast, not a probability of adoption, and it does not separate automation from augmentation.
Task-level exposure
13 rated tasks · 0 tasks with β ≥ 0.5 (0.0%)
β = direct exposure (E1) + 0.5 × exposure when tools are available (E2), per the source repository's definition.
- Source unit: O*NET 27.2 tasks → O*NET 31.0 occupation code
- 1 rated task is not in the O*NET 31.0 task list; its score is kept as published for O*NET 27.2.
- Source
- OpenAI "GPTs are GPTs" exposure rubric
- Release
- gh-main-0471612
- License
- MIT License, Copyright (c) 2024 OpenAI
Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime.
| Task (O*NET 27.2) | βE1 + 0.5 × E2 |
|---|---|
Use knives, cleavers, meat saws, bandsaws, or other equipment to perform meat cutting and trimming.O*NET Task ID 8795 | 0.0 |
Clean, trim, slice, and section carcasses for future processing.O*NET Task ID 8796 | 0.0 |
Cut and trim meat to prepare for packing.O*NET Task ID 8797 | 0.0 |
Remove parts, such as skin, feathers, scales or bones, from carcass.O*NET Task ID 8798 | 0.0 |
Inspect meat products for defects, bruises or blemishes and remove them along with any excess fat.O*NET Task ID 8799 | 0.0 |
Produce hamburger meat and meat trimmings.O*NET Task ID 8800 | 0.0 |
Process primal parts into cuts that are ready for retail use.O*NET Task ID 8801 | 0.0 |
Obtain and distribute specified meat or carcass.O*NET Task ID 8802 | 0.0 |
Separate meats and byproducts into specified containers and seal containers.O*NET Task ID 8803 | 0.0 |
Weigh meats and tag containers for weight and contents.O*NET Task ID 8804 | 0.0 |
Clean and salt hides.O*NET Task ID 8805 | 0.0 |
Prepare sausages, luncheon meats, hot dogs, and other fabricated meat products, using meat trimmings and hamburger meat.O*NET Task ID 8806 | 0.0 |
Prepare ready-to-heat foods by filleting meat or fish or cutting it into bite-sized pieces, preparing and adding vegetables or applying sauces or breading.O*NET Task ID 8807 | 0.0 |
β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.
Data sources & licenses — O*NET®, Eloundou et al. (2023): see full notices on the Credits page
All O*NET 31.0 task statements (12)
All O*NET 31.0 task statements for this occupation (English, as published; task type core or supplemental). Exposure values are not listed here; they are in the table above, next to each task statement as worded in the O*NET version each source used.
| Task (O*NET 31.0) | Type |
|---|---|
| Use knives, cleavers, meat saws, bandsaws, or other equipment to perform meat cutting and trimming. | Core |
| Cut and trim meat to prepare for packing. | Core |
| Inspect meat products for defects, bruises or blemishes and remove them along with any excess fat. | Core |
| Separate meats and byproducts into specified containers and seal containers. | Core |
| Weigh meats and tag containers for weight and contents. | Core |
| Clean, trim, slice, and section carcasses for future processing. | Supplemental |
| Remove parts, such as skin, feathers, scales or bones, from carcass. | Supplemental |
| Produce hamburger meat and meat trimmings. | Supplemental |
| Process primal parts into cuts that are ready for retail use. | Supplemental |
| Obtain and distribute specified meat or carcass. | Supplemental |
| Clean and salt hides. | Supplemental |
| Prepare ready-to-heat foods by filleting meat or fish or cutting it into bite-sized pieces, preparing and adding vegetables or applying sauces or breading. | Supplemental |
0.89/ 3· Robot exposure index
Scale, basis and source
Each physical task is graded 0–3 by the setting in which robots that have been deployed, sold or demonstrated could do it (0 none · 1 purpose-built robot settings such as a fenced machine cell or a bottling line · 2 structured facilities such as a hospital pharmacy or a container port · 3 unstructured settings such as a private home or a construction site), and the grades are averaged by share of working time
Physical tasks among this occupation's O*NET 29.3 tasks
Anthropic estimated the grades and time shares with Claude Opus 5 using web search, as of 2026.
The robot exposure index is a different measure from the AI exposure figures on this site and cannot be added to or compared with them. It does not measure actual adoption or cost, and 0 also covers occupations with no physical tasks.
Tier of each physical task
Robot environment tiers (E0–E3)
E0 noneDetails
Rated not doable by robots that have been deployed, sold or demonstrated, even in a purpose-built setting
E1 purpose-built robot settingsDetails
Rated doable in a setting built around the machine, such as a fenced machine cell or a bottling line
E2 structured facilitiesDetails
Rated doable in a human work facility that an institution keeps to a working standard, such as a hospital pharmacy or a container port
E3 unstructured settingsDetails
Rated doable in a setting that no institution keeps to a working standard, such as a private home or a construction site
Only tasks classified as physical are listed; other tasks have no tier in the source.
| Task (O*NET 29.3) | Robot environment tier |
|---|---|
| Use knives, cleavers, meat saws, bandsaws, or other equipment to perform meat cutting and trimming. | E1 purpose-built robot settings |
| Cut and trim meat to prepare for packing. | E1 purpose-built robot settings |
| Inspect meat products for defects, bruises or blemishes and remove them along with any excess fat. | E0 none |
| Separate meats and byproducts into specified containers and seal containers. | E1 purpose-built robot settings |
| Weigh meats and tag containers for weight and contents. | E1 purpose-built robot settings |
| Clean, trim, slice, and section carcasses for future processing. | E1 purpose-built robot settings |
| Remove parts, such as skin, feathers, scales or bones, from carcass. | E1 purpose-built robot settings |
| Produce hamburger meat and meat trimmings. | E1 purpose-built robot settings |
| Process primal parts into cuts that are ready for retail use. | E1 purpose-built robot settings |
| Obtain and distribute specified meat or carcass. | E1 purpose-built robot settings |
| Clean and salt hides. | E1 purpose-built robot settings |
| Prepare ready-to-heat foods by filleting meat or fish or cutting it into bite-sized pieces, preparing and adding vegetables or applying sauces or breading. | E1 purpose-built robot settings |
Occupation information
Employment outlook (BLS)
- Employment, 2025
- 150K
- Projected employment, 2035
- 158K
- Change (2025–35)
- +5.7%
- Median annual wage, 2025
- $38,300
- Typical education needed for entry
- No formal educational credential
Korea classification links (KSCO)
Links from the current release of the Korea Occupation Direct Crosswalk v1.1, made by AI Changing Work. Relation values are read from the O*NET-SOC occupation side.
| KSCO code | KSCO title | Relation | Status |
|---|---|---|---|
| 71032 | 도축원 | Overlapping, not the same | confirmed |
| 71092 | 수산물 가공 및 염장원 | Overlapping, not the same | confirmed |
| 81132 | 어패류가공 기계 조작원 | Related, not a match | confirmed |
Relation and status definitions(kr-direct v1.1)
ILO occupational description
AI Changing Work links the ISCO-08 unit groups below to this occupation by applying the U.S. Bureau of Labor Statistics crosswalks (2018 SOC to 2010 SOC, 2010 SOC to ISCO-08) as published, without case-by-case selection; each link may be whole or partial.
- ISCO-08 7511Butchers, Fishmongers and Related Food Preparers
The definition, tasks and examples below are the ILO's description of that unit group, not of this occupation.
Butchers, fishmongers and related food preparers slaughter animals, clean, cut and dress meat and fish, remove bones and prepare related food items, or preserve meat, fish and other foods and food products by drying, salting or smoking.
Tasks
- (a) slaughtering animals;
- (b) flaying and trimming carcasses;
- (c) boning, cutting and dressing meat and fish for sale or further processing;
- (d) preparing ingredients and making sausages and similar products using chopping, mixing and shaping machines;
- (e) curing meat, fish and other foods;
- (f) operating smokehouses or ovens to smoke meat, fish and other foodstuffs;
- (g) cooking or in other ways preparing meat, fish and related food items for sale;
- (h) selling meat or fish to customers, including wrapping, weighing and labelling products, and receiving payment.
Example occupations
Butcher · Fish filleter · Fishmonger · Slaughterer
Sources: ILO ISCO-08 — details: Credits
ESCO occupational vocabulary
Each entry below is matched to this occupation in the published ESCO-O*NET Crosswalk (version 1, 2022). The match types are that crosswalk's; the wording is AI Changing Work's.
- fish trimmerESCO 7511.3This occupation is broader
Fish trimmers cut off fish heads and remove organs from the body for fish and seafood production. They remove organs by scraping and washing, cut out areas presenting defects, and package the processed fish in appropriate containers.
- meat cutterESCO 7511.4This occupation is broader
Meat cutters cut carcasses of animals into large and smaller parts for further processing. They remove bones from pre-processed carcasses of animals either manually or using machines.
- butcherESCO 7511.1Overlapping, not the same
Butchers order, inspect and buy meat to prepare it and sell it as consumable meat products. They perform activities such as cutting, trimming, boning, tying, and grinding beef, pork, and poultry meat. They prepare those mentioned sorts of meat for consumption.
- halal butcherESCO 7511.1.1Overlapping, not the same
Halal butchers order, inspect and buy meat to prepare it and sell it as consumable meat products in accordance with Islamic practices. They perform activities such as cutting, trimming, boning, tying, and grinding beef and poultry meat. They prepare halal meat for consumption.
- kosher butcherESCO 7511.1.2Overlapping, not the same
Kosher butchers order, inspect and buy meat to prepare it and sell it as consumable meat products in accordance with Jewish practices. They perform activities such as cutting, trimming, boning, tying, and grinding meats from kosher animals such as cows, sheep and goats. They prepare kosher meat for consumption.
- meat preparations operatorESCO 7511.5Overlapping, not the same
Meat preparations operators prepare fresh meat with ingredients such as spices, herbs or additives in order to make ready-for-sale meat preparations.
Source: European Commission, DG EMPL — ESCO API 2026-08-08 (bridge v1.2.1)
License: CC BY 4.0 (EU Reuse Notice)
ESCO reuse terms and the modification notice are in Credits.
France classification links (ROME)
AI Changing Work's links between this occupation and ROME 4.0 job profiles, judged with AI models. Relations are read from this occupation's side. Links marked “provisional” were adopted on the judgments of two judges from the same model family (Claude) alone, or by an operator rule applied to their judgments, so they rest on weaker evidence than confirmed links.
| ROME code | ROME title (French) | Relation |
|---|---|---|
| H2103 | Opérateur / Opératrice de transformation des viandes | This occupation is broaderprovisional |
| H2101 | Ouvrier / Ouvrière d'abattoir | Overlapping, not the sameprovisional |
| H2107 | Opérateur / Opératrice de préparation de poissons et produits de la mer | Overlapping, not the sameprovisional |
| D1105 | Poissonnier / Poissonnière | Related, not a matchprovisional |
Source: France Travail — Répertoire Opérationnel des Métiers et des Emplois (ROME 4.0), version 61, last updated 15 June 2026 (https://www.data.gouv.fr/datasets/repertoire-operationnel-des-metiers-et-des-emplois-rome). Licence Ouverte 2.0.
ROME codes and titles are reproduced unchanged; the links to O*NET-SOC occupations are AI Changing Work's own judgment and are not a France Travail correspondence.
(AI Changing Work link release: fr-direct v1)
Spain classification links (CNO-11)
AI Changing Work's links between this occupation and CNO-11 occupations, judged with AI models. Relations are read from this occupation's side.
| CNO-11 code | CNO-11 title (Spanish) | Relation |
|---|---|---|
| 7701 | Matarifes y trabajadores de las industrias cárnicas | This occupation is narrowerprovisional |
| 7702 | Trabajadores de las industrias del pescado | Related, not a matchprovisional |
| 9700 | Peones de las industrias manufactureras | Related, not a matchprovisional |
Source: Instituto Nacional de Estadística (INE), National Classification of Occupations 2011 (CNO-11, Royal Decree 1591/2010) — www.ine.es · Licensed CC BY 4.0. CNO-11 codes and Spanish titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own judgment and are not an INE correspondence.
(AI Changing Work link release: es-direct v1)
Germany classification links (KldB)
AI Changing Work's links between this occupation and KldB occupations, judged with AI models. Relations are read from this occupation's side.
| KldB code | KldB title (German) | Relation |
|---|---|---|
| 29232 | Berufe in der Fleischverarbeitung - fachlich ausgerichtete Tätigkeiten | Overlapping, not the same |
| 29201 | Berufe in der Lebensmittelherstellung (ohne Spezialisierung) - Helfer-/Anlerntätigkeiten | Related, not a match |
| 29242 | Berufe in der Fischverarbeitung - fachlich ausgerichtete Tätigkeiten | Related, not a match |
Source: © Statistik der Bundesagentur für Arbeit — Klassifikation der Berufe 2010 – überarbeitete Fassung 2020, https://statistik.arbeitsagentur.de. KldB codes and titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own mapping (eigene Zuordnung) and are not a Bundesagentur für Arbeit correspondence.
(AI Changing Work link release: de-direct v1)
Japan classification links (JSCO)
AI Changing Work's links between this occupation and JSCO occupations, judged with AI models. Relations are read from this occupation's side.
| JSCO code | JSCO title (Japanese) | Relation |
|---|---|---|
| 533 | 食料品製造従事者 | This occupation is narrowerprovisional |
| 539 | その他の製品製造・加工処理従事者（金属製品を除く） | Related, not a matchprovisional |
Source: Ministry of Internal Affairs and Communications (MIC), Japan Standard Occupational Classification (Dec. 2009, MIC Notification No. 555). JSCO codes and Japanese titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own judgment and are not a MIC correspondence.
(AI Changing Work link release: jp-direct v1)
Sources, licenses and AI Changing Work's modification and translation notices for this page: Credits & sources