48
/100

SOC 53-7041

Hoist and Winch Operators

ElevatedFrey/Osborne: 65.0%

Risk Score

โš ๏ธ

48/100

Elevated

US Employment

๐Ÿ‘ฅ

2,480

Total workers

Median Wage

๐Ÿ’ฐ

$52K

$34K โ€“ $116K

Projected Growth

๐Ÿ“ˆ

-1.1%

2023-2033 (BLS)

GenAI Exposure

๐Ÿค–

10/100

Low exposure

How we calculate these numbers โ†’

๐Ÿ’ก Hoist and Winch Operators face a risk score of 48/100 โ€” 4 points above the national average of 44. With only 10/100 GenAI exposure, most core tasks remain resistant to current AI capabilities. See our methodology โ†’

๐Ÿ’ก Workers in this field earn $52K ($6K above the national median). The 3 recommended career transitions all maintain competitive wages while reducing automation exposure. Explore transition paths โ†’

๐Ÿ” AI Impact Analysis

With a risk score of 48/100, Hoist and Winch Operators faces moderate automation pressure. While tasks like autonomous vehicle and self-driving truck technology are increasingly handled by AI, the role retains significant human elements. The 2,480 workers in this occupation should focus on strengthening skills in emergency situation response and quick decision-making and navigating unpredictable road and weather conditions to stay ahead. The role will likely evolve rather than disappear.

Will AI Replace Hoist and Winch Operators?

Read our full analysis with verdict, risk factors, safe tasks, and career transition paths โ†’

โš ๏ธ Top Risk Factors

1

Autonomous vehicle and self-driving truck technology

2

AI route optimization reducing dispatcher roles

3

AI traffic management and fleet coordination

4

Automated warehouse sorting and loading systems

๐Ÿ›ก๏ธ Tasks Safe from Automation

โœ“

Emergency situation response and quick decision-making

โœ“

Navigating unpredictable road and weather conditions

โœ“

Customer interaction and conflict resolution during delivery

โœ“

Manual loading of irregular and fragile cargo

๐Ÿ“Š Task Automation Breakdown

Based on O*NET task analysis and GenAI exposure scoring. Shows the estimated proportion of this occupation's core tasks that are automatable by current AI, augmented by AI tools, or require essential human skills.

๐Ÿ“‹ O*NET Task Profile

โ€ข

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.

โ€ข

Start engines of hoists or winches and use levers and pedals to wind or unwind cable on drums.

โ€ข

Observe equipment gauges and indicators and hand signals of other workers to verify load positions or depths.

โ€ข

Operate compressed air, diesel, electric, gasoline, or steam-driven hoists or winches to control movement of cableways, cages, derricks, draglines, loaders, railcars, or skips.

โ€ข

Move or reposition hoists, winches, loads and materials, manually or using equipment and machines such as trucks, cars, and hand trucks.

๐Ÿ’ป Technology Skills

โ€ข

Spreadsheet software

โ€ข

Word processing software

๐ŸŽ“ Key Knowledge Areas

โ€ข

Mechanical

โ€ข

Customer and Personal Service

โ€ข

English Language

โ€ข

Public Safety and Security

โ€ข

Transportation

๐Ÿ“Š vs National Average

Median Wage$52K
+$6K

National avg: $46K

Risk Score48/100
+4

National avg: 44/100

GenAI Exposure10/100
-28

National avg: 38/100

Projected Growth-1.1%
-4.8%

National avg: 3.7%

๐Ÿ”„ Career Transition Paths

OccupationRiskWageOverlap
First-Line Supervisors of Transportation and Material Moving Workers, Except Aircraft Cargo Handling Supervisors25$62K76%
Aircraft Cargo Handling Supervisors29$64K83%
Air Transportation Workers31$107K79%