Cleaners of Vehicles and Equipment
Transportation and Material Moving Occupations- O*NET-SOC code
- 53-7061.00
Wash or otherwise clean vehicles, machinery, and other equipment. Use such materials as water, cleaning agents, brushes, cloths, and hoses.
- 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
0.09–0.12· 2 ISCO-08 groups
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.
ILO value for each linked ISCO-08 group
- ISCO-08 9112Cleaners and Helpers in Offices, Hotels and Other Establishments0.12
- ISCO-08 9122Vehicle Cleaners0.09
Task-level exposure
Show 19 hidden tasks21 rated tasks · 2 tasks with β ≥ 0.5 (9.5%)
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. 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 |
|---|---|
Maintain inventories of supplies.O*NET Task ID 5005 | 1.0 |
Inspect parts, equipment, or vehicles for cleanliness, damage, and compliance with standards or regulations.O*NET Task ID 4992 | 0.5 |
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 (20)
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 |
|---|---|
| Inspect parts, equipment, or vehicles for cleanliness, damage, and compliance with standards or regulations. | Core |
| Scrub, scrape, or spray machine parts, equipment, or vehicles, using scrapers, brushes, clothes, cleaners, disinfectants, insecticides, acid, abrasives, vacuums, or hoses. | Core |
| Mix cleaning solutions, abrasive compositions, or other compounds, according to formulas. | Core |
| Press buttons to activate cleaning equipment or machines. | Core |
| Clean and polish vehicle windows. | Core |
| Rinse objects and place them on drying racks or use cloth, squeegees, or air compressors to dry surfaces. | Core |
| Drive vehicles to or from workshops or customers' workplaces or homes. | Core |
| Turn valves or handles on equipment to regulate pressure or flow of water, air, steam, or abrasives from sprayer nozzles. | Core |
| Pre-soak or rinse machine parts, equipment, or vehicles by immersing objects in cleaning solutions or water, manually or using hoists. | Core |
| Monitor operation of cleaning machines and stop machines or notify supervisors when malfunctions occur. | Core |
| Connect hoses or lines to pumps or other equipment. | Core |
| Maintain inventories of supplies. | Core |
| Apply paints, dyes, polishes, reconditioners, waxes, or masking materials to vehicles to preserve, protect, or restore color or condition. | Core |
| Turn valves or disconnect hoses to eliminate water, cleaning solutions, or vapors from machinery or tanks. | Core |
| Sweep, shovel, or vacuum loose debris or salvageable scrap into containers and remove containers from work areas. | Core |
| Lubricate machinery, vehicles, or equipment or perform minor repairs or adjustments, using hand tools. | Supplemental |
| Disassemble and reassemble machines or equipment or remove and reattach vehicle parts or trim, using hand tools. | Supplemental |
| Transport materials, equipment, or supplies to or from work areas, using carts or hoists. | Supplemental |
| Clean the plastic work inside cars, using paintbrushes. | Supplemental |
| Fit boot spoilers, side skirts, or mud flaps to cars. | Supplemental |
1.00/ 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 |
|---|---|
| Inspect parts, equipment, or vehicles for cleanliness, damage, and compliance with standards or regulations. | E0 none |
| Scrub, scrape, or spray machine parts, equipment, or vehicles, using scrapers, brushes, clothes, cleaners, disinfectants, insecticides, acid, abrasives, vacuums, or hoses. | E1 purpose-built robot settings |
| Mix cleaning solutions, abrasive compositions, or other compounds, according to formulas. | E2 structured facilities |
| Press buttons to activate cleaning equipment or machines. | E2 structured facilities |
| Clean and polish vehicle windows. | E0 none |
| Rinse objects and place them on drying racks or use cloth, squeegees, or air compressors to dry surfaces. | E1 purpose-built robot settings |
| Drive vehicles to or from workshops or customers' workplaces or homes. | E2 structured facilities |
| Turn valves or handles on equipment to regulate pressure or flow of water, air, steam, or abrasives from sprayer nozzles. | E1 purpose-built robot settings |
| Pre-soak or rinse machine parts, equipment, or vehicles by immersing objects in cleaning solutions or water, manually or using hoists. | E1 purpose-built robot settings |
| Monitor operation of cleaning machines and stop machines or notify supervisors when malfunctions occur. | E2 structured facilities |
| Connect hoses or lines to pumps or other equipment. | E1 purpose-built robot settings |
| Maintain inventories of supplies. | E1 purpose-built robot settings |
| Apply paints, dyes, polishes, reconditioners, waxes, or masking materials to vehicles to preserve, protect, or restore color or condition. | E1 purpose-built robot settings |
| Turn valves or disconnect hoses to eliminate water, cleaning solutions, or vapors from machinery or tanks. | E2 structured facilities |
| Sweep, shovel, or vacuum loose debris or salvageable scrap into containers and remove containers from work areas. | E1 purpose-built robot settings |
| Lubricate machinery, vehicles, or equipment or perform minor repairs or adjustments, using hand tools. | E0 none |
| Disassemble and reassemble machines or equipment or remove and reattach vehicle parts or trim, using hand tools. | E0 none |
| Transport materials, equipment, or supplies to or from work areas, using carts or hoists. | E2 structured facilities |
| Clean the plastic work inside cars, using paintbrushes. | E1 purpose-built robot settings |
| Fit boot spoilers, side skirts, or mud flaps to cars. | E1 purpose-built robot settings |
Occupation information
Employment outlook (BLS)
- Employment, 2025
- 420K
- Projected employment, 2035
- 436K
- Change (2025–35)
- +3.9%
- Median annual wage, 2025
- $35,830
- 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 |
|---|---|---|---|
| 94121 | 운송장비 청소원 | This occupation is broader | confirmed |
| 94122 | 시설장비 청소원 | This occupation is broader | confirmed |
| 79919 | 그 외 세정원 | 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 9112Cleaners and Helpers in Offices, Hotels and Other Establishments
- ISCO-08 9122Vehicle Cleaners
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.
- vehicle cleanerESCO 9122.1Same scope
Vehicle cleaners clean and polish surfaces of external parts and interiors of vehicles.
- aircraft groomerESCO 9112.1Overlapping, not the same
Aircraft groomers clean aircraft cabins and airplanes after usage. They vacuum or sweep the interior of cabin, brushes debris from seats, and arranges seat belts. They clean trash and debris from seat pockets and arranged in-flight magazines, safety cards, and sickness bags. They also clean galleys and lavatories.
- train cleanerESCO 9112.6Overlapping, not the same
Train cleaners keep the interiors of trains tidy and clean. They clean out the bins in the different compartments, and perform other cleaning activities such as hoovering, mopping and deep cleaning.
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 |
|---|---|---|
| I1611 | Préparateur / Préparatrice de véhicules automobiles | Overlapping, not the same |
| K2204 | Agent / Agente de nettoyage industriel | Related, not a match |
| D1304 | Responsable de station de lavage | 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 |
|---|---|---|
| 9222 | Limpiadores de vehículos | Same scope |
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 |
|---|---|---|
| 54152 | Berufe in der Fahrzeugreinigung - fachlich ausgerichtete Tätigkeiten | This occupation is broader |
| 54101 | Berufe in der Reinigung (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 |
|---|---|---|
| 719 | その他の清掃従事者 | This occupation is narrowerprovisional |
| 739 | その他の運搬・清掃・包装等従事者 | 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