Hoist and winch operators
SOC Code: 53-7041
Hoist and winch operators carries a 21% AI exposure score (Medium automation risk), with a median annual wage of $52,310 and -1.1% projected employment growth from 2024 to 2034 (BLS), affecting approximately 2,700 workers. Full task breakdown, skills, and employer data are below.
Proportion of tasks susceptible to AI automation (O*NET analysis)
At 21% AI exposure, Hoist and winch operators sits 16 points below the 37.2% average across 832 U.S. occupations - more exposed than 8% of them. It ranks among the more AI-resilient roles in the dataset.
Career outlook score
51/100
Hoist and winch operators, weighted across 3 of 3 tracked dimensions
A weighted composite of median wage, projected growth, and AI-automation security (inverted exposure), each benchmarked against every other tracked occupation. It describes this occupation's standing across those three dimensions, not a guarantee of future outcomes.
- Median wage D $52,310
Annual median wage, percentile rank vs all tracked occupations
- Projected growth F -1.1%
Projected employment change, 2024-2034, BLS Employment Projections
- AI exposure (inverted) A+ 21% exposure
Lower O*NET task-automability scores lower risk; this dimension scores security, not exposure
Home health and personal care aides is #1 of 832 occupations by employment (4.3M, AI exposure rank #392 at 35%) vs. Bookkeeping, accounting, and auditing clerks #1 by AI task exposure (95%, employment rank #17 at 1.6M).
Automation-risk inventory
Exclusive cut of 832 occupations by PlainWorkforce automation-risk band. Orthogonal to the continuous AI-exposure distribution chart below and to this occupation's single risk badge, this is the corpus band mix, with Hoist and winch operators in the Medium band.
Credential × growth standing
Open entry with non-declining BLS pace
Hoist and winch operators keeps an No credential bar (109 of 832) and sits in Slow growth (245 of 832). Lower formal gates with a non-shrinking employment line - skill and AI desks matter more than credentials here.
Where Hoist and winch operators sits among all occupations
AI-exposure score distribution across 832 U.S. occupations (O*NET task analysis). This occupation is marked in rose.
Where Hoist and winch operators sits by AI exposure
AI-exposure score distribution across U.S. occupations (O*NET task analysis)
21% Among the lowest lower than 92% of 832 occupations
Occupations, banded by AI-exposure score
Each bar is a band; taller bars hold more occupations. The dashed line + filled bar mark this entry. Hover or tap any bar for its full count and share, and where it sits relative to this entry.
Source O*NET task data (U.S. Department of Labor) · BLS 2024–2034
Source: O*NET task data (U.S. Department of Labor); AI-exposure scores are PlainWorkforce's analysis. As of BLS 2024–2034.
Hoist and winch operators vs. its occupational neighbors
AI exposure (horizontal) vs projected 2024–2034 growth (vertical) for occupations in the same SOC group. Hoist and winch operators is marked in rose; the top-left corner is the most future-proof.
Source: BLS Employment Projections 2024–2034 (growth) and O*NET (AI-exposure analysis by PlainWorkforce).
Employment Projections
Where This Score Comes From
Hoist and winch operators's Medium automation-risk tier is computed from O*NET Database 30.0 task-level analysis, where each documented task the occupation performs is evaluated against current generative AI, robotic process automation, and machine-learning capabilities. A score below 40% reflects tasks anchored in physical dexterity, unstructured environments, or high-touch human interaction that current AI cannot reliably replicate.
The employment, wage, and education figures above come from a second, separate federal source: BLS Employment Projections 2024–2034, matched to the O*NET task data by Standard Occupational Classification (SOC 53-7041) code, with the wage figure cross-validated against the BLS Occupational Employment and Wage Statistics (OEWS) May 2024 survey. BLS figures are presented exactly as published, with no adjustment on our part; the SOC-code match is what lets Hoist and winch operators be compared directly against every other tracked occupation on the same basis, not just roles that happen to share a job title.
For career planners, this profile should be read alongside the task, skill, and knowledge breakdowns below and the list of employers whose workforce composition includes Hoist and winch operators. Adjacent occupations shown further down offer lateral moves that preserve industry knowledge while potentially reducing exposure.
Education & Entry Requirements
Top Tasks (O*NET)
- 1. 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.
- 2. Apply hand or foot brakes and move levers to lock hoists or winches.
- 3. Start engines of hoists or winches and use levers and pedals to wind or unwind cable on drums.
- 4. Observe equipment gauges and indicators and hand signals of other workers to verify load positions or depths.
- 5. Operate compressed air, diesel, electric, gasoline, or steam-driven hoists or winches to control movement of cableways, cages, derricks, draglines, loaders, railcars, or skips.
- 6. Oil winch drums so that cables will wind smoothly.
- 7. Move or reposition hoists, winches, loads and materials, manually or using equipment and machines such as trucks, cars, and hand trucks.
- 8. Climb ladders to position and set up vehicle-mounted derricks.
- 9. Select loads or materials according to weight and size specifications.
- 10. Repair, maintain, and adjust equipment, using hand tools.
Key Skills Required
- Critical Thinking
- Monitoring
- Operations Monitoring
- Time Management
- Active Listening
- Operation and Control
- Complex Problem Solving
- Judgment and Decision Making
- Speaking
- Social Perceptiveness
Knowledge Areas
- Mechanical
- Customer and Personal Service
- English Language
- Public Safety and Security
- Transportation
- Administration and Management
- Engineering and Technology
- Education and Training
- Mathematics
- Production and Processing
Frequently Asked Questions
Will AI replace Hoist and winch operators?
Hoist and winch operators has an AI exposure score of 21%, indicating a medium level of automation risk. The majority of tasks in this role require human judgment, creativity, or physical presence that AI cannot easily replicate.
What is the job outlook for Hoist and winch operators?
According to BLS Employment Projections 2024-2034, Hoist and winch operators is projected to decline by 1.1% over the decade. Current employment stands at approximately 2,700 workers.
What skills are needed for Hoist and winch operators?
Key skills for Hoist and winch operators include Critical Thinking, Monitoring, Operations Monitoring, and others. Typical entry-level education is No formal educational credential.
How much do Hoist and winch operators earn?
The median annual wage for Hoist and winch operators is $52,310, according to BLS Occupational Employment and Wage Statistics (May 2024). Actual earnings vary by location, experience, industry, and employer. The BLS publishes detailed wage percentiles by region in its Occupational Employment and Wage Statistics program.
What education is required for Hoist and winch operators?
The typical entry-level education for Hoist and winch operators is No formal educational credential. Employers generally expect None of related work experience. On-the-job training typically involves Short-term on-the-job training. Requirements can vary by employer and specialization.
Which companies employ Hoist and winch operators?
Hoist and winch operators roles exist across many industries and employers. Workforce composition is estimated from BLS industry-occupation employment distributions matched to SEC-registered public companies.
AI Exposure Rating
Medium automation risk based on 10 analyzed tasks. Most tasks require human judgment and are resistant to automation.
Nationwide occupations with similar workforce profiles
Two data-derived peer sets for Hoist and winch operators: AI-exposure neighbors and BLS 2034 growth neighbors (distinct comparison neighborhoods, cross-occupation).
Similar AI exposure score
Nearest O*NET task-automability scores nationwide (21% here).
- Athletes and sports competitors · AI exposure 21%
- Automotive body and related repairers · AI exposure 21%
- Automotive glass installers and repairers · AI exposure 21%
- Boilermakers · AI exposure 21%
Similar projected growth (2024–2034)
Nearest BLS employment change rates nationwide (-1.1% here).
- Extruding and forming machine setters, operators, and tenders, synthetic and glass fibers · growth -1.1%
- Nuclear engineers · growth -1.1%
- Fine artists, including painters, sculptors, and illustrators · growth -1.2%
- Legal support workers, all other · growth -1.2%
Peers are nearest-neighbor matches on published BLS + O*NET metrics among occupations with ≥10,000 workers in 2024; corpus ranks above sort the full tracked set.
Related Occupations
Showing 6 of 28 occupations with a comparable automation-risk profile.
What to do with this
Use Hoist and winch operators' numbers above to compare, not just read in isolation.
- Compare Hoist and winch operators side by side against another occupation on wage, growth, and AI exposure. Workforce comparison tool
- Understand how the AI exposure score above is actually calculated before treating it as a verdict. Reading AI exposure scores
- See the full ranked list of occupations with the lowest automation exposure nationwide. Safest occupations from AI
AI exposure scores estimate task automatability from O*NET data; they are not a certainty of job loss, and BLS growth projections are estimates, not guarantees.
Data sources: Bureau of Labor Statistics Employment Projections 2024–2034 and O*NET Database 30.0. Employment figures are rounded. Wage data from BLS Occupational Employment Statistics (OES).