JobBreak

Transportation and Material Moving · United States (national)

Hoist and Winch Operators

How exposed this work is to automation, shown as ranges with the reasoning and sources.

The short version: this role is highly exposed to automation, and the bigger shift looks near-term. It is a sourced range, not a verdict, and the detail is below.

Built on O*NET tasks, BLS pay and projections, and peer-reviewed AI-exposure research. Sources shown. Data snapshot SNAPSHOT-2026-11-06. How it works
9.5 of 100
AI / softwarerange 0.0 to 21.5
67.8 of 100
Physical / roboticsrange 55.8 to 79.8

When the change is likely

change likely 0y 5y 10y 15y 20+y

Near-term, high local demand stable

What to do about it

Use AI to outpace AI.

Strategies to protect your livelihood, most important first.

1
Act within the next 1 to 2 years
Displacement for this role is near-term. Start a concrete reskilling plan now, while you still have income and leverage.
2
Move up from the task to the system
Robotics targets the physical work. Shift toward supervising, maintaining, or programming the automation instead of competing with it.
3
Pivot toward Crane and Tower Operators
It is skill-adjacent and less exposed (54.6 vs 68). A lateral move now beats a forced one later.
4
Build a financial buffer
Keep 6 to 12 months of expenses and diversify your income, so a disruption is a setback rather than a catastrophe.
5
Add a recognised credential
A certification or license raises the bar against automation and signals value in a tightening market.

Which of my tasks are exposed

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.
67.8
Start engines of hoists or winches and use levers and pedals to wind or unwind cable on drums.
67.8
Observe equipment gauges and indicators and hand signals of other workers to verify load positions or depths.
67.8
Operate compressed air, diesel, electric, gasoline, or steam-driven hoists or winches to control movement of cableways, cages, derricks, draglines, loaders, railcars, or skips.
67.8
Move or reposition hoists, winches, loads and materials, manually or using equipment and machines such as trucks, cars, and hand trucks.
67.8
Select loads or materials according to weight and size specifications.
67.8
Signal and assist other workers loading or unloading materials.
67.8
Attach, fasten, and disconnect cables or lines to loads, materials, and equipment, using hand tools.
67.8

Longer, orange bars are more automatable; short green bars are resistant.

What is driving my result

lowers risk
raises risk
Task: 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.
Task: Start engines of hoists or winches and use levers and pedals to wind or unwind cable on drums.

Lower-risk adjacent roles

Crane and Tower Operators
54.6
Excavating and Loading Machine and Dragline Operators, Surface Mining
55.8
Operating Engineers and Other Construction Equipment Operators
59.2
Industrial Truck and Tractor Operators
61.2

A full, ranked mitigation plan is part of the paid tiers.

How this score is calculated

  1. Map Hoist and Winch Operators to its standard O*NET task list (8 core tasks).
  2. Score each task for AI/software exposure (Eloundou et al. 2023) and physical/robotics exposure (an O*NET work-context proxy), each 0 to 100.
  3. The two axis scores are the task averages: AI 9.5, robotics 67.8.
  4. The timeline comes from the higher axis (67.8), shifted for local demand (stable), and seniority. It is read against your remaining working years.
  5. Ranges are about ±12 points. A backtest against real BLS employment change shows the risk ranking holds in aggregate, but individual outcomes are predicted weakly, so results are ranges, never a flat verdict.

Sources: O*NET, Eloundou et al. (2023), GPTs are GPTs, O*NET Work Context, BLS CPI-U, BLS OEWS. Snapshot SNAPSHOT-2026-11-06. Full method and backtest on How it works.

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