Dishwashers

Food Preparation and Serving Related Occupations

O*NET-SOC code: 35-9021.00

Clean dishes, kitchen, food preparation equipment, or utensils.

Data source: BLSPublished: 2026-08
Low· relative
LowFour relative bandsVery high
Group-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
Source dataset (XLSX download)
Data source: AnthropicPublished: 2026-03
0.000
0.000Range of values carried here0.745
Scale, 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
Source dataset (CSV download)
Data source: ILOPublished: 2025
0.13
0.09Range of values carried here0.70
Group-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
Source dataset (PDF download)

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
All rated tasks are in the O*NET 31.0 task list.

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. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.

Task (O*NET 27.2)	βE1 + 0.5 × E2
Wash dishes, glassware, flatware, pots, or pans, using dishwashers or by hand. O*NET Task ID 11186	0.0
Place clean dishes, utensils, or cooking equipment in storage areas. O*NET Task ID 11187	0.0
Maintain kitchen work areas, equipment, or utensils in clean and orderly condition. O*NET Task ID 11188	0.0
Stock supplies, such as food or utensils, in serving stations, cupboards, refrigerators, or salad bars. O*NET Task ID 11189	0.0
Sweep or scrub floors. O*NET Task ID 11190	0.0
Clean garbage cans with water or steam. O*NET Task ID 11191	0.0
Sort and remove trash, placing it in designated pickup areas. O*NET Task ID 11192	0.0
Clean or prepare various foods for cooking or serving. O*NET Task ID 11193	0.0
Set up banquet tables. O*NET Task ID 11194	0.0
Transfer supplies or equipment between storage and work areas, by hand or using hand trucks. O*NET Task ID 11195	0.0
Receive and store supplies. O*NET Task ID 11196	0.0
Prepare and package individual place settings. O*NET Task ID 11197	0.0
Load or unload trucks that deliver or pick up food or supplies. O*NET Task ID 11198	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 (13)

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
Wash dishes, glassware, flatware, pots, or pans, using dishwashers or by hand.	Core
Place clean dishes, utensils, or cooking equipment in storage areas.	Core
Maintain kitchen work areas, equipment, or utensils in clean and orderly condition.	Core
Stock supplies, such as food or utensils, in serving stations, cupboards, refrigerators, or salad bars.	Core
Sweep or scrub floors.	Core
Clean garbage cans with water or steam.	Core
Sort and remove trash, placing it in designated pickup areas.	Core
Clean or prepare various foods for cooking or serving.	Core
Transfer supplies or equipment between storage and work areas, by hand or using hand trucks.	Core
Receive and store supplies.	Core
Set up banquet tables.	Supplemental
Prepare and package individual place settings.	Supplemental
Load or unload trucks that deliver or pick up food or supplies.	Supplemental

Anthropic, "What work can robots do?"2026-09

1.49/ 3· Robot exposure index

0 none3 unstructured settings

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.

Source dataset

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
Wash dishes, glassware, flatware, pots, or pans, using dishwashers or by hand.	E2 structured facilities
Place clean dishes, utensils, or cooking equipment in storage areas.	E1 purpose-built robot settings
Maintain kitchen work areas, equipment, or utensils in clean and orderly condition.	E1 purpose-built robot settings
Stock supplies, such as food or utensils, in serving stations, cupboards, refrigerators, or salad bars.	E1 purpose-built robot settings
Sweep or scrub floors.	E1 purpose-built robot settings
Clean garbage cans with water or steam.	E1 purpose-built robot settings
Sort and remove trash, placing it in designated pickup areas.	E1 purpose-built robot settings
Transfer supplies or equipment between storage and work areas, by hand or using hand trucks.	E1 purpose-built robot settings
Receive and store supplies.	E1 purpose-built robot settings
Clean or prepare various foods for cooking or serving.	E1 purpose-built robot settings
Set up banquet tables.	E0 none
Prepare and package individual place settings.	E1 purpose-built robot settings
Load or unload trucks that deliver or pick up food or supplies.	E2 structured facilities

Employment outlook (BLS)

Employment, 2025: 480K
Projected employment, 2035: 476K
Change (2025–35): -1%
Median annual wage, 2025: $34,810
Typical education needed for entry: No formal educational credential

lowest $30,890median wage across 825 detailed occupations, BLS EP 2025–35highest $559,030

Source: U.S. Bureau of Labor Statistics, Employment Projections 2025–35 — Employment by detailed occupation, 2025 and projected 2035

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
95220	주방 보조원	This occupation is narrower	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 9412Kitchen Helpers

The definition, tasks and examples below are the ILO's description of that unit group, not of this occupation.

Kitchen helpers clear tables, clean kitchen areas, wash dishes, prepare ingredients and perform other duties to assist workers who prepare or serve food and beverages.

Tasks

(a) cleaning kitchens, food preparation areas and service areas;
(b) assisting cooks and chefs in preparation of food by washing, peeling, chopping, cutting, measuring and mixing ingredients;
(c) assembling dishes for service;
(d) unpacking checking, transferring, weighing and storing supplies in refrigerators, cupboards and other storage areas;
(e) washing dishes and cooking utensils and putting them away;
(f) preparing, cooking, toasting and heating simple food items.

Example occupations

Hand dishwasher · Kitchen assistant · Kitchen hand · Kitchen porter · Kitchen steward · Pantry attendant

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.

kitchen porterESCO 9412.2Same scope
Kitchen porters wash and clean kitchen areas, including pots, pans, utensils, cutlery and dishes. They prepare the kitchen area before service, and receive and store supplies.

Source: European Commission, DG EMPL — ESCO API 2026-08-08 (bridge v1.2.1)

License: CC BY 4.0 (EU Reuse Notice)

View original

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
G1605	Plongeur officier / Plongeuse officière de cuisine	Same scopeprovisional

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
9310	Ayudantes de cocina	This occupation is narrowerprovisional

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
63301	Berufe im Gastronomieservice (ohne Spezialisierung) - Helfer-/Anlerntätigkeiten	This occupation is narrower
29301	Köche/Köchinnen (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
739	その他の運搬・清掃・包装等従事者	This occupation is narrower

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