Slaughterers and Meat Packers
Production Occupations- O*NET-SOC code
- 51-3023.00
Perform nonroutine or precision functions involving the preparation of large portions of meat. Work may include specialized slaughtering tasks, cutting standard or premium cuts of meat for marketing, making sausage, or wrapping meats. Work typically occurs in slaughtering, meat packing, or wholesale establishments.
- Data source: BLSPublished: 2026-08
Low· 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
15 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 |
|---|---|
Remove bones, and cut meat into standard cuts in preparation for marketing.O*NET Task ID 13986 | 0.0 |
Cut, trim, skin, sort, and wash viscera of slaughtered animals to separate edible portions from offal.O*NET Task ID 13987 | 0.0 |
Slaughter animals in accordance with religious law, and determine that carcasses meet specified religious standards.O*NET Task ID 13988 | 0.0 |
Slit open, eviscerate, and trim carcasses of slaughtered animals.O*NET Task ID 13989 | 0.0 |
Tend assembly lines, performing a few of the many cuts needed to process a carcass.O*NET Task ID 13990 | 0.0 |
Sever jugular veins to drain blood and facilitate slaughtering.O*NET Task ID 13991 | 0.0 |
Shave or singe and defeather carcasses, and wash them in preparation for further processing or packaging.O*NET Task ID 13992 | 0.0 |
Trim, clean, or cure animal hides.O*NET Task ID 13993 | 0.0 |
Shackle hind legs of animals to raise them for slaughtering or skinning.O*NET Task ID 13994 | 0.0 |
Skin sections of animals or whole animals.O*NET Task ID 13995 | 0.0 |
Trim head meat, and sever or remove parts of animals' heads or skulls.O*NET Task ID 13996 | 0.0 |
Saw, split, or scribe carcasses into smaller portions to facilitate handling.O*NET Task ID 13997 | 0.0 |
Grind meat into hamburger, and into trimmings used to prepare sausages, luncheon meats, and other meat products.O*NET Task ID 13998 | 0.0 |
Stun animals prior to slaughtering.O*NET Task ID 13999 | 0.0 |
Wrap dressed carcasses or meat cuts.O*NET Task ID 14000 | 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 (14)
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 |
|---|---|
| Remove bones, and cut meat into standard cuts in preparation for marketing. | Supplemental |
| Cut, trim, skin, sort, and wash viscera of slaughtered animals to separate edible portions from offal. | Supplemental |
| Slit open, eviscerate, and trim carcasses of slaughtered animals. | Supplemental |
| Tend assembly lines, performing a few of the many cuts needed to process a carcass. | Supplemental |
| Sever jugular veins to drain blood and facilitate slaughtering. | Supplemental |
| Shave or singe and defeather carcasses, and wash them in preparation for further processing or packaging. | Supplemental |
| Trim, clean, or cure animal hides. | Supplemental |
| Shackle hind legs of animals to raise them for slaughtering or skinning. | Supplemental |
| Skin sections of animals or whole animals. | Supplemental |
| Trim head meat, and sever or remove parts of animals' heads or skulls. | Supplemental |
| Saw, split, or scribe carcasses into smaller portions to facilitate handling. | Supplemental |
| Grind meat into hamburger, and into trimmings used to prepare sausages, luncheon meats, and other meat products. | Supplemental |
| Stun animals prior to slaughtering. | Supplemental |
| Wrap dressed carcasses or meat cuts. | Supplemental |
0.85/ 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 |
|---|---|
| Remove bones, and cut meat into standard cuts in preparation for marketing. | E1 purpose-built robot settings |
| Cut, trim, skin, sort, and wash viscera of slaughtered animals to separate edible portions from offal. | E0 none |
| Slit open, eviscerate, and trim carcasses of slaughtered animals. | E0 none |
| Tend assembly lines, performing a few of the many cuts needed to process a carcass. | E2 structured facilities |
| Sever jugular veins to drain blood and facilitate slaughtering. | E0 none |
| Shave or singe and defeather carcasses, and wash them in preparation for further processing or packaging. | E1 purpose-built robot settings |
| Trim, clean, or cure animal hides. | E1 purpose-built robot settings |
| Shackle hind legs of animals to raise them for slaughtering or skinning. | E0 none |
| Skin sections of animals or whole animals. | E0 none |
| Trim head meat, and sever or remove parts of animals' heads or skulls. | E0 none |
| Saw, split, or scribe carcasses into smaller portions to facilitate handling. | E1 purpose-built robot settings |
| Grind meat into hamburger, and into trimmings used to prepare sausages, luncheon meats, and other meat products. | E1 purpose-built robot settings |
| Stun animals prior to slaughtering. | E1 purpose-built robot settings |
| Wrap dressed carcasses or meat cuts. | E1 purpose-built robot settings |
Occupation information
Employment outlook (BLS)
- Employment, 2025
- 71K
- Projected employment, 2035
- 73K
- Change (2025–35)
- +2%
- Median annual wage, 2025
- $40,130
- 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 | This occupation is broader | confirmed |
| 71039 | 그 외 정육 가공 및 도축 관련 종사원 | This occupation is broader | confirmed |
| 81131 | 육류가공 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.
- slaughtererESCO 7511.6Same scope
Slaughterers slaughter animals and process carcasses for further processing and distribution.
- halal slaughtererESCO 7511.6.1This occupation is broader
Halal slaughterers slaughter animals and process carcasses of halal meat from cows and chickens for further processing and distribution. They slaughter animals as stated in Islamic law and ensure that the animals are fed, slaughtered and hung up accordingly.
- kosher slaughtererESCO 7511.6.2This occupation is broader
Kosher slaughterers slaughter animals and process carcasses of kosher meat for further processing and distribution. They slaughter animals as stated in Jewish law and according to rituals.
- meat cutterESCO 7511.4Overlapping, not the same
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.
- prepared meat operatorESCO 8160.47Overlapping, not the same
Prepared meat operators process meat either by hand or using meat machines such as meat grinding, crushing or mixing machines. They perform preservation processes such as pasteurising, salting, drying, freeze-drying, fermenting and smoking. Prepared meat operators strive to keep meat free from germs and other health risks for a longer period than fresh meat.
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 |
|---|---|---|
| H2101 | Ouvrier / Ouvrière d'abattoir | This occupation is broaderprovisional |
| H2103 | Opérateur / Opératrice de transformation des viandes | Overlapping, not the sameprovisional |
| D1101 | Boucher / Bouchère | 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 |
| 8160 | Operadores de máquinas para elaborar productos alimenticios, bebidas y tabaco | 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 | This occupation is narrower |
| 29201 | Berufe in der Lebensmittelherstellung (ohne Spezialisierung) - Helfer-/Anlerntätigkeiten | 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 | Related, not a matchprovisional |
| 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