AI exposure by occupation, O*NET 53-7021.00
Will AI replace Crane and Tower Operators?
Crane and Tower Operators: AI can already handle 1 of 11 tasks; most of the work is hands-on, and the part AI can address mostly needs an efficient-tier model.
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Every task, scored
The 11 tasks O*NET 30.3 lists for Crane and Tower Operators, from most to least exposed. 1 reach 60 or more, the level at which AI already handles a task.
| Task | AI exposure | Evidence | Model tier |
|---|---|---|---|
| Review daily work or delivery schedules to determine orders, sequences of deliveries, or special loading instructions. | Estimated | Efficient | |
| Inspect and adjust crane mechanisms or lifting accessories to prevent malfunctions or damage. | Estimated | Efficient | |
| Inspect cables or grappling devices for wear and install or replace cables, as needed. | Estimated | Efficient | |
| Clean, lubricate, and maintain mechanisms such as cables, pulleys, or grappling devices, making repairs, as necessary. | Estimated | Efficient | |
| Inspect bundle packaging for conformance to regulations or customer requirements, and remove and batch packaging tickets. | Estimated | Efficient | |
| Direct helpers engaged in placing blocking or outrigging under cranes. | Estimated | No tier | |
| Load or unload bundles from trucks, or move containers to storage bins, using moving equipment. | Estimated | No tier | |
| Weigh bundles, using floor scales, and record weights for company records. | Estimated | No tier | |
| Determine load weights and check them against lifting capacities to prevent overload. | Estimated | No tier | |
| Move levers, depress foot pedals, or turn dials to operate cranes, cherry pickers, electromagnets, or other moving equipment for lifting, moving, or placing loads. | Estimated | No tier | |
| Direct truck drivers backing vehicles into loading bays and cover, uncover, or secure loads for delivery. | Estimated | No tier |
Observed: scored from AI use recorded in the Anthropic Economic Index (June 2026 release), 0 of 11 tasks. Estimated: scored from the task's O*NET 30.3 work activity, 11 of 11. Importance is O*NET's 1 to 5 rating of how central the task is. Model tier is the lowest tier that can do the task under the published rubric; "No tier" marks hands-on work.
The model tier this role needs
An efficient-tier model or lower covers 46% of the role's importance-weighted task work. 46% of the work is something AI can address at some tier, and 54% is hands-on.
Efficient, standard and frontier tiers come from the JobRoute model tier reference. The recommended tier is the lowest one that covers 80% of the work AI can address. How the method works.
Wages, employment and outlook
- US employment
- 42,890
- Median annual wage
- $68,080
- Middle half of earners
- $52,600 to $83,200
- Projected change, 2024 to 2034
- +3.0%
Employment and wages: BLS Occupational Employment and Wage Statistics, May 2025, national. Projection: BLS Employment Projections 2024 to 2034.
Adjacent roles
The occupations that reuse the most of this role's skills, with the usual time to move. These are the first places to look when you plan to redeploy or retrain people in this role.
- Hoist and Winch Operators 71% skill overlap, about 10 months to move Exposure20
- Operating Engineers and Other Construction Equipment Operators 67% skill overlap, about 12 months to move Exposure18
- Industrial Truck and Tractor Operators 66% skill overlap, about 12 months to move Exposure26
- Pump Operators, Except Wellhead Pumpers 61% skill overlap, about 14 months to move Exposure18
- Bridge and Lock Tenders 60% skill overlap, about 14 months to move Exposure17
Skill overlap and transition time from the JobRoute role adjacency graph on O*NET 30.3 skills.
Questions about Crane and Tower Operators and AI
Will AI replace Crane and Tower Operators?
AI already handles 1 of the 11 tasks O*NET lists for this occupation, at a task exposure of 60 or more, and the role's importance-weighted exposure is 19 out of 100. JobRoute scores tasks, not whole jobs, so the score shows how much of the work changes rather than whether the job disappears. BLS projects employment to change by +3.0% from 2024 to 2034.
What is the AI exposure of Crane and Tower Operators?
19 out of 100 on JobRoute's task exposure measure, the importance-weighted average of the role's O*NET task scores. Higher means more of the work is AI-doable today. 0 of the 11 task scores are observed in the Anthropic Economic Index (June 2026 release), and the other 11 are estimated from each task's O*NET work activity.
Which Crane and Tower Operators tasks can AI already do?
The tasks with the highest exposure are: Review daily work or delivery schedules to determine orders, sequences of deliveries, or special loading instructions. It is the only task that reach 60 or more.
What AI model tier does this role need?
An efficient-tier model or lower covers 46% of the role's importance-weighted task work, and 54% is hands-on work that no model tier covers. JobRoute assigns each task the lowest tier that can do it under a published rubric and recommends the lowest tier that covers 80% of the work AI can address.
How many people work as Crane and Tower Operators, and what do they earn?
42,890 people in the United States, with a median annual wage of $68,080 (BLS Occupational Employment and Wage Statistics, May 2025). BLS Employment Projections expect a change of +3.0% from 2024 to 2034.
How to cite
Data version 2026-11-02, JobRoute method v1.0.0. Download all occupations or this occupation as JSON. Methodology.
JobRoute (2026). AI exposure: Crane and Tower Operators. Data version 2026-11-02, method v1.0.0. Built on O*NET 30.3, BLS OEWS May 2025 and the Anthropic Economic Index (June 2026). CC BY 4.0. https://www.jobroute.ai/jobs/crane-and-tower-operators
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