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 →Hoist and Winch Operators
Occupation · SOC 53-7041.00
Operate or tend hoists or winches to lift and pull loads using power-operated cable equipment.
Also called: Hoist Operator · Hoistman · Material Handler · Service Operator · Winch Derrick Operator · Air Hoist Operator · Air Lift Operator · Boat Hoist Operator · Boat Loader · Boat Puller · Bridge Rigger · Building Rigger
Job family: Transportation and Material Moving Occupations
Take this to your AI
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-53-7041-00/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.
- Declining employment outlook (-1.1% by 2034)
- 300 openings/yr
- Low AI exposure
- Median pay $52,310/yr
- Work is mostly on-site (not teleworkable)
- 2013 flagged this for computerization (55th); today's AI task-overlap is comparatively low (9th)
9th-percentile task overlap — yet about 300 openings a year (-1.1% 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 | 18th | -1.0 | |
| LLM task exposure, γ (OpenAI / Eloundou) Low | 3rd | 0.0 | |
| AI assistant applicability (Microsoft) Low | 17th | 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 · 55th 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 | Declining · -1.1% by 2034 |
| Projected annual openings | 300 |
| Employment 2024 → 2034 | 2,700 → 2,700 |
“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 occupation below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.
Hoist and Winch Operators sits at the 25th percentile of 427
occupations on the global GenAI task-exposure gradient
— exposure rose from 2023 to 2025. Each dot is one occupation; the
ringed one is this work. Exposure is task overlap, not automation or jobs lost.
18% mean task exposure (2025)
25th percentile of 427 placed occupations
+1 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Crane, hoist and related plant operators · 8343 | 18% | 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 13 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Move levers, pedals, and throttles to stop, start, and regulate speeds of hoist or winch drums in response to hand, bell, buzzer, telephone, loud-speaker, or whistle signals, or by observing dial indicators or cable marks. Core · importance 4.6
- Apply hand or foot brakes and move levers to lock hoists or winches. Supplemental · importance 4.5
- Start engines of hoists or winches and use levers and pedals to wind or unwind cable on drums. Core · importance 4.5
- Observe equipment gauges and indicators and hand signals of other workers to verify load positions or depths. Core · importance 4.4
- Oil winch drums so that cables will wind smoothly. Supplemental · importance 4.3
- Operate compressed air, diesel, electric, gasoline, or steam-driven hoists or winches to control movement of cableways, cages, derricks, draglines, loaders, railcars, or skips. Core · importance 4.3
- Move or reposition hoists, winches, loads and materials, manually or using equipment and machines such as trucks, cars, and hand trucks. Core · importance 4.1
- Climb ladders to position and set up vehicle-mounted derricks. Supplemental · importance 4.1
- Select loads or materials according to weight and size specifications. Core · importance 4.1
- Repair, maintain, and adjust equipment, using hand tools. Supplemental · importance 4.0
- Signal and assist other workers loading or unloading materials. Core · importance 3.9
- Tend auxiliary equipment, such as jacks, slings, cables, or stop blocks, to facilitate moving items or materials for further processing. Supplemental · importance 3.9
- Attach, fasten, and disconnect cables or lines to loads, materials, and equipment, using hand tools. Core · importance 3.7
Work activities
- Operate cranes, hoists, or other moving or lifting equipment.
- Monitor equipment gauges or displays to ensure proper operation.
- Move materials, equipment, or supplies.
- Position material handling equipment.
- Select project materials.
- Load shipments, belongings, or materials.
- Communicate with others to coordinate material handling or movement.
- Connect cables or electrical lines.
- Maintain material moving equipment in good working condition.
- Climb ladders or vehicles to perform duties.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Abilities
| Problem Sensitivity | 3.9 | |
| Arm-Hand Steadiness | 3.6 | |
| Control Precision | 3.6 | |
| Reaction Time | 3.6 | |
| Depth Perception | 3.6 | |
| Multilimb Coordination | 3.5 | |
| Near Vision | 3.5 | |
| Oral Comprehension | 3.4 | |
| Oral Expression | 3.4 | |
| Deductive Reasoning | 3.4 | |
| Selective Attention | 3.4 | |
| Manual Dexterity | 3.4 | |
| Speech Recognition | 3.4 | |
| Inductive Reasoning | 3.3 | |
| Perceptual Speed | 3.3 | |
| Visualization | 3.3 | |
| Rate Control | 3.3 | |
| Far Vision | 3.3 | |
| Hearing Sensitivity | 3.3 | |
| Speech Clarity | 3.3 | |
| Information Ordering | 3.1 | |
| Finger Dexterity | 3.1 | |
| Extent Flexibility | 3.1 | |
| Gross Body Equilibrium | 3.1 | |
| Category Flexibility | 3.0 | |
| Response Orientation | 3.0 |
Essential skills
| Critical Thinking | 3.8 | |
| Monitoring | 3.6 | |
| Active Listening | 3.4 | |
| Speaking | 3.1 |
Transferable skills
Knowledge
| Mechanical | 3.1 |
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 Word | Word processing software | Hot technology |
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 2 — Job Zone 1-2: Very Little to Some Preparation Needed
- Education
- Usually requires a high school diploma or GED, though some occupations may not.
- Typical entry-level education
- No formal educational credential · BLS, the typical path — not a requirement
- Related experience
- Some occupations may need little or no previous experience; others require several months to a year of experience. For example, landscaping and groundskeeping workers might require very little training or previous experience, while agricultural equipment operators can benefit from on-the job training.
- Preparation level
- SVP (Below 6.0) — total schooling plus on-the-job experience.
What to study: Transportation and Materials Moving . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Education of current workers
Share of people in this occupation at each level of education.
| Less than a High School Diploma | 26.7% | |
| Post-Secondary Certificate | 23.5% | |
| Some College Courses | 8.6% |
Interests & work styles
The interests and personal qualities O*NET associates with people who do this work.
Career interests (Holland / RIASEC)
| Realistic | 6.9 | |
| Conventional | 3.3 | |
| Investigative | 1.6 | |
| Social | 1.4 | |
| Enterprising | 1.4 |
Interest areas
| Physical/Manual Labor | 4.9 | |
| Transportation/Machine Operation | 4.0 | |
| Mechanics/Electronics | 3.1 | |
| Engineering | 2.3 | |
| Construction/Woodwork | 2.0 | |
| Nature/Outdoors | 1.2 | |
| Agriculture | 1.1 |
Work styles
| Dependability | 2.4 | |
| Cautiousness | 2.3 | |
| Attention to Detail | 1.9 | |
| Stress Tolerance | 1.2 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $33,910 |
| 25th percentile | $39,220 |
| Median (50th) | $52,310 |
| 75th percentile | $90,200 |
| 90th percentile | $116,120 |
| People employed | 2,480 |
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 |
|---|---|---|
| Manufacturing · Sector | 830 | $40,110 |
| Transportation and Warehousing · Sector | 540 | $76,720 |
| Mining, Quarrying, and Oil and Gas Extraction · Sector | 170 | $66,280 |
| Construction · Sector | 140 | $61,480 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 120 | $34,780 |
| Temporary Help Services · National industry | 110 | $35,970 |
| Agriculture, Forestry, Fishing and Hunting · Sector | 60 | $56,760 |
| Professional, Scientific, and Technical Services · Sector | 30 | $74,650 |
| Wholesale Trade · Sector | — | $33,280 |
| Arts, Entertainment, and Recreation · Sector | — | $104,500 |
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 |
|---|---|---|
| Mining, Quarrying, and Oil and Gas Extraction · Sector | 18.43× | 170 |
| Transportation and Warehousing · Sector | 4.54× | 540 |
| Manufacturing · Sector | 4.04× | 830 |
| Temporary Help Services · National industry | 2.58× | 110 |
| Construction · Sector | 1.07× | 140 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 0.83× | 120 |
Related occupations
Part of the Advanced Manufacturing and Construction career clusters.
- Riggers · 49-9096.00 Compare →
- Industrial Truck and Tractor Operators · 53-7051.00 Compare →
- Crane and Tower Operators · 53-7021.00 Compare →
- Operating Engineers and Other Construction Equipment Operators · 47-2073.00 Compare →
- Excavating and Loading Machine and Dragline Operators, Surface Mining · 47-5022.00 Compare →
- Mobile Heavy Equipment Mechanics, Except Engines · 49-3042.00 Compare →
- Roustabouts, Oil and Gas · 47-5071.00 Compare →
- Pile Driver Operators · 47-2072.00 Compare →
- Maintenance Workers, Machinery · 49-9043.00 Compare →
- Laborers and Freight, Stock, and Material Movers, Hand · 53-7062.00 Compare →
- Woodworking Machine Setters, Operators, and Tenders, Except Sawing · 51-7042.00 Compare →
- Loading and Moving Machine Operators, Underground Mining · 47-5044.00 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 Hoist and Winch Operators — 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 2 — Job Zone 1-2: Very Little to Some Preparation Needed · preparation tier
- Transportation and Materials Moving · field of study
Zoom out
On the global GenAI exposure gradient this work sits around the 25th percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Hoist and Winch Operators show 9th-percentile AI task overlap — and about 300 annual U.S. openings
- Hoist and Winch Operators rank in the 9th 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 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 declining (-1.1%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $52,310, across about 2,480 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Hoist and Winch Operators show 9th-percentile AI task overlap — and about 300 annual U.S. openings • Hoist and Winch Operators rank in the 9th 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 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 declining (-1.1%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $52,310, across about 2,480 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "Hoist and Winch Operators". https://singulariki.com/roles/role-53-7041-00 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. "Hoist and Winch Operators." 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-53-7041-00
APA
Singulariki. (2026). Hoist and Winch Operators. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-53-7041-00
BibTeX
@misc{singulariki-role-53-7041-00,
title = {Hoist and Winch Operators},
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-53-7041-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.