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 →Janitors and Cleaners, Except Maids and Housekeeping Cleaners
Occupation · SOC 37-2011.00
Keep buildings in clean and orderly condition. Perform heavy cleaning duties, such as cleaning floors, shampooing rugs, washing walls and glass, and removing rubbish. Duties may include tending furnace and boiler, performing routine maintenance activities, notifying management of need for repairs, and cleaning snow or debris from sidewalk.
Also called: Cleaner · Custodial Worker · Custodian · Janitor · Building Custodian · Building Services Technician (Building Services Tech) · Building Services Worker · Facilities Worker · Heavy Duty Custodian · School Custodian · Airport Attendant · Alley Cleaner
Job family: Building and Grounds Cleaning and Maintenance Occupations
Take this to your AI
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-37-2011-00/context.md directly.
AI work map
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.
Market signal
Independent published positions, read together — not a forecast.
- About average employment outlook (+2.0% by 2034)
- 351,300 openings/yr
- Low AI exposure
- Median pay $35,930/yr
- Work is mostly on-site (not teleworkable)
- 2013 flagged this for computerization (56th); today's AI task-overlap is comparatively low (10th)
10th-percentile task overlap — yet about 351,300 openings a year (+2% projected, BLS) . What exposure means →
AI & job outlook
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.
Exposure to current AI
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.) Low | 6th | -1.4 | |
| LLM task exposure, γ (OpenAI / Eloundou) Low | 3rd | 0.0 | |
| AI assistant applicability (Microsoft) Low | 32nd | 0.1 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.0), with simple added tooling (β 0.0), and including AI-powered software (γ 0.0). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.
This job mostly cannot be done remotely (Dingel–Neiman) — its hands-on tasks sit outside what software-based AI reaches.
Historical automation estimate (2013)
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 0.7 · 56th percentile among occupations · Moderate
Job outlook
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | About average · +2.0% by 2034 |
| Projected annual openings | 351,300 |
| Employment 2024 → 2034 | 2,447,700 → 2,495,500 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
Where this work sits on the global GenAI gradient
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 3 occupations below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.
Janitors and Cleaners, Except Maids and Housekeeping Cleaners sits at the 32nd percentile of 427
occupations on the global GenAI task-exposure gradient
— exposure eased from 2023 to 2025. Each dot is one occupation; the
ringed one is this work. Exposure is task overlap, not automation or jobs lost.
20% mean task exposure (2025)
32nd percentile of 427 placed occupations
−4 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Building Caretakers · 5153 | 27% | Minimal |
| Cleaners and Helpers in Offices, Hotels and Other Establishments · 9112 | 12% | Not exposed |
| Window Cleaners · 9123 | 11% | Not exposed |
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.
Tasks
All 23 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Service, clean, or supply restrooms. Core · importance 4.2
- Gather and empty trash. Core · importance 4.2
- Clean building floors by sweeping, mopping, scrubbing, or vacuuming. Core · importance 4.2
- Monitor building security and safety by performing tasks such as locking doors after operating hours or checking electrical appliance use to ensure that hazards are not created. Supplemental · importance 4.2
- Notify managers concerning the need for major repairs or additions to building operating systems. Core · importance 4.2
- Follow procedures for the use of chemical cleaners and power equipment to prevent damage to floors and fixtures. Core · importance 4.2
- Mix water and detergents or acids in containers to prepare cleaning solutions, according to specifications. Core · importance 4.0
- Clean windows, glass partitions, or mirrors, using soapy water or other cleaners, sponges, or squeegees. Core · importance 3.8
- Dust furniture, walls, machines, or equipment. Core · importance 3.7
- Requisition supplies or equipment needed for cleaning and maintenance duties. Core · importance 3.7
- Strip, seal, finish, and polish floors. Core · importance 3.7
- Remove snow from sidewalks, driveways, or parking areas, using snowplows, snow blowers, or snow shovels, or spread snow-melting chemicals. Supplemental · importance 3.5
- Make adjustments or minor repairs to heating, cooling, ventilating, plumbing, or electrical systems. Supplemental · importance 3.5
- Clean and polish furniture and fixtures. Core · importance 3.5
- Drive vans, industrial trucks, or other vehicles required to travel to, or to perform, cleaning work. Supplemental · importance 3.4
- Move heavy furniture, equipment, or supplies, either manually or with hand trucks. Core · importance 3.4
- Set up, arrange, or remove decorations, tables, chairs, ladders, or scaffolding to prepare facilities for events, such as banquets or meetings. Supplemental · importance 3.4
- Spray insecticides or fumigants to prevent insect or rodent infestation. Supplemental · importance 3.4
- Clean chimneys, flues, and connecting pipes, using power or hand tools. Supplemental · importance 3.2
- Mow or trim lawns or shrubbery, using mowers or hand or power trimmers, and clear debris from grounds. Supplemental · importance 3.1
- Steam-clean or shampoo carpets. Core · importance 3.0
- Clean and restore building interiors damaged by fire, smoke, or water, using commercial cleaning equipment. Supplemental
- Clean laboratory equipment, such as glassware or metal instruments, using solvents, brushes, rags, or power cleaning equipment. Supplemental
Work activities
- Monitor building premises to ensure occupant or visitor safety.
- Remove debris from work sites.
- Trim trees or other vegetation.
- Operate grounds maintenance equipment.
- Drive trucks or other vehicles to or at work sites.
- Clean facilities or sites.
- Dispose of trash or waste materials.
- Clean building walls or flooring.
- Prepare chemicals for work application.
- Confer with coworkers to coordinate maintenance or cleaning activities.
- Select equipment, materials, or supplies for cleaning or maintenance activities.
- Clean furniture or fixtures.
- Move furniture.
- Decorate indoor or outdoor spaces.
- Clean equipment or supplies.
- Remove snow.
- Treat facilities to eliminate pests.
- Maintain equipment or systems to ensure proper functioning.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Knowledge
| Public Safety and Security | 3.4 | |
| Administration and Management | 3.1 | |
| English Language | 2.9 | |
| Customer and Personal Service | 2.7 | |
| Transportation | 2.3 | |
| Law and Government | 2.3 |
Abilities
| Trunk Strength | 3.3 | |
| Near Vision | 3.3 | |
| Oral Comprehension | 3.0 | |
| Oral Expression | 3.0 | |
| Problem Sensitivity | 3.0 | |
| Arm-Hand Steadiness | 3.0 | |
| Manual Dexterity | 3.0 | |
| Static Strength | 3.0 | |
| Extent Flexibility | 3.0 | |
| Information Ordering | 2.9 | |
| Selective Attention | 2.9 | |
| Multilimb Coordination | 2.9 | |
| Speech Clarity | 2.9 | |
| Deductive Reasoning | 2.8 | |
| Finger Dexterity | 2.8 | |
| Stamina | 2.8 | |
| Gross Body Coordination | 2.8 | |
| Far Vision | 2.8 | |
| Speech Recognition | 2.8 | |
| Category Flexibility | 2.6 | |
| Control Precision | 2.6 | |
| Inductive Reasoning | 2.5 |
Essential skills
| Active Listening | 3.0 | |
| Speaking | 3.0 | |
| Critical Thinking | 2.8 | |
| Monitoring | 2.8 | |
| Active Learning | 2.6 | |
| Reading Comprehension | 2.5 | |
| Writing | 2.4 |
Transferable skills
| Coordination | 2.8 | |
| Time Management | 2.8 | |
| Social Perceptiveness | 2.6 | |
| Service Orientation | 2.5 | |
| Judgment and Decision Making | 2.4 |
Skills in demand
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
Tools & technology
| Example | Category | |
|---|---|---|
| Microsoft Excel | Spreadsheet software | Hot technology |
| Microsoft Office software | Office suite software | Hot technology |
| Microsoft Outlook | Electronic mail software | Hot technology |
| Microsoft Word | Word processing software | Hot technology |
| Eko | Desktop communications software | |
| Squeegee | Cloud-based data access and sharing software |
Work context
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.
How to get in
- Job zone
- Zone 3 — Job Zone Three: Medium Preparation Needed
- Education
- Most occupations in this zone require training in vocational schools, related on-the-job experience, or an associate's degree.
- Typical entry-level education
- No formal educational credential · BLS, the typical path — not a requirement
- Related experience
- Previous work-related skill, knowledge, or experience is required for these occupations. For example, an electrician must have completed three or four years of apprenticeship or several years of vocational training, and often must have passed a licensing exam, in order to perform the job.
- Preparation level
- SVP (6.0 to < 7.0) — total schooling plus on-the-job experience.
Education of current workers
Share of people in this occupation at each level of education.
| Less than a High School Diploma | 13.5% | |
| Post-Doctoral Training | 0.6% |
Interests & work styles
The interests and personal qualities O*NET associates with people who do this work.
Career interests (Holland / RIASEC)
| Realistic | 6.7 | |
| Conventional | 4.6 | |
| Social | 2.1 | |
| Enterprising | 1.7 | |
| Investigative | 1.1 |
Interest areas
Work styles
| Dependability | 2.1 | |
| Attention to Detail | 1.4 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $27,570 |
| 25th percentile | $30,830 |
| Median (50th) | $35,930 |
| 75th percentile | $41,650 |
| 90th percentile | $49,040 |
| People employed | 2,199,900 |
Industries that employ this occupation
Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.
| Industry | Workers | National median pay |
|---|---|---|
| Administrative and Support and Waste Management and Remediation Services · Sector | 947,960 | $34,970 |
| Educational Services · Sector | 402,130 | $37,540 |
| Health Care and Social Assistance · Sector | 164,670 | $36,930 |
| Retail Trade · Sector | 113,700 | $34,560 |
| Accommodation and Food Services · Sector | 110,950 | $36,350 |
| Real Estate and Rental and Leasing · Sector | 72,210 | $38,600 |
| Manufacturing · Sector | 71,700 | $38,690 |
| Arts, Entertainment, and Recreation · Sector | 53,350 | $34,470 |
| Temporary Help Services · National industry | 52,950 | $35,200 |
| Other Services (except Public Administration) · Sector | 51,590 | $35,270 |
| Transportation and Warehousing · Sector | 44,540 | $45,660 |
| Full-Service Restaurants · National industry | 21,870 | $35,240 |
Where this work is most concentrated
Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).
| Industry | Concentration | Workers |
|---|---|---|
| Administrative and Support and Waste Management and Remediation Services · Sector | 7.36× | 947,960 |
| Casino Hotels · National industry | 4.46× | 21,460 |
| Fitness and Recreational Sports Centers · National industry | 2.23× | 20,090 |
| Real Estate and Rental and Leasing · Sector | 2.14× | 72,210 |
| Educational Services · Sector | 2.07× | 402,130 |
| Arts, Entertainment, and Recreation · Sector | 1.42× | 53,350 |
| Temporary Help Services · National industry | 1.4× | 52,950 |
| Theater Companies and Dinner Theaters · National industry | 0.85× | 880 |
Related occupations
Part of the Hospitality, Events, & Tourism career cluster.
- Maids and Housekeeping Cleaners · 37-2012.00 Compare →
- Cleaners of Vehicles and Equipment · 53-7061.00 Compare →
- Laundry and Dry-Cleaning Workers · 51-6011.00 Compare →
- Septic Tank Servicers and Sewer Pipe Cleaners · 47-4071.00 Compare →
- Dishwashers · 35-9021.00 Compare →
- Recycling and Reclamation Workers · 53-7062.04 Compare →
- Maintenance and Repair Workers, General · 49-9071.00 Compare →
- Floor Sanders and Finishers · 47-2043.00 Compare →
- Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders · 51-9192.00 Compare →
- Landscaping and Groundskeeping Workers · 37-3011.00 Compare →
- Carpet Installers · 47-2041.00 Compare →
- Hazardous Materials Removal Workers · 47-4041.00 Compare →
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
What you can do with this
Options the data surfaces for Janitors and Cleaners, Except Maids and Housekeeping Cleaners — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Skills that travel
Capabilities this work builds that are used across many other occupations.
Adjacent roles
Occupations O*NET rates as related — the nearby moves on the map.
Paths in
How people typically prepare for this work.
- No formal educational credential · typical entry level
- Job zone 3 — Job Zone Three: Medium Preparation Needed · preparation tier
Zoom out
On the global GenAI exposure gradient this work sits around the 32nd percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Janitors and Cleaners, Except Maids and Housekeeping Cleaners show 10th-percentile AI task overlap — and about 351,300 annual U.S. openings
- Janitors and Cleaners, Except Maids and Housekeeping Cleaners rank in the 10th percentile (Low 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
- The occupation is projected to see about 351,300 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI.BLS Employment Projections 2024–34
- BLS projects employment to be about average (+2%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $35,930, across about 2,199,900 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Janitors and Cleaners, Except Maids and Housekeeping Cleaners show 10th-percentile AI task overlap — and about 351,300 annual U.S. openings • Janitors and Cleaners, Except Maids and Housekeeping Cleaners rank in the 10th percentile (Low 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) • The occupation is projected to see about 351,300 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34) • BLS projects employment to be about average (+2%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $35,930, across about 2,199,900 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "Janitors and Cleaners, Except Maids and Housekeeping Cleaners". https://singulariki.com/roles/role-37-2011-00 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.
Sources for this page
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.
- O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
- BLS Occupational Employment and Wage Statistics (OEWS) May 2024 U.S. Bureau of Labor Statistics
- BLS Employment Projections 2024–2034 U.S. Bureau of Labor Statistics
- Microsoft “Working with AI” working-with-ai Microsoft Research
- “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic
- AI Occupational Exposure (AIOE) Felten, Raj & Seamans academic
- ILO / Gmyrek et al. GenAI exposure gradient 2025 International Labour Organization
- IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022 Institute for Structural Research (IBS)
- Frey & Osborne (2013) frey-osborne-automation academic
- Dingel & Neiman (2020) dingel-neiman-workathome academic
Data compiled June 2, 2026. Figures are estimates, not advice.
Cite this page
Plain
Singulariki. "Janitors and Cleaners, Except Maids and Housekeeping Cleaners." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Microsoft “Working with AI” working-with-ai; “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-37-2011-00
APA
Singulariki. (2026). Janitors and Cleaners, Except Maids and Housekeeping Cleaners. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-37-2011-00
BibTeX
@misc{singulariki-role-37-2011-00,
title = {Janitors and Cleaners, Except Maids and Housekeeping Cleaners},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Microsoft “Working with AI” working-with-ai; “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-37-2011-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.