Will AI replace Rail Yard Engineers, Dinkey Operators, and Hostlers?
AI reaches little of this job’s work.
5/100
Low exposure
More exposed to AI than 11% of US workers.
- AI already used in
- 0% of the work
- As AI tools mature: up to
- 11% of the work
What the job involves
Drive switching or other locomotive or dinkey engines within railroad yard, industrial plant, quarry, construction project, or similar location.
Where AI reaches the work
The job’s main tasks, heaviest first, by how far AI reaches them.
Within reach(3)
- Report arrival and departure times, train delays, work order completion, and time on duty.
- Read switching instructions and daily car schedules to determine work to be performed, or receive orders from yard conductors.
- Record numbers of cars available, numbers of cars sent to repair stations, and types of service needed.
Out of reach(20)
- Inspect engines before and after use to ensure proper operation.
- Apply and release hand brakes.
- Drive engines within railroad yards or other establishments to couple, uncouple, or switch railroad cars.
- Observe water levels and oil, air, and steam pressure gauges to ensure proper operation of equipment.
- Signal crew members for movement of engines or trains, using lanterns, hand signals, radios, or telephones.
and 15 more
Also called
Yard Engineer · Hostler · Railcar Switcher · Car Mover · Coal Trammer · Diesel Dinkey Engineer · Diesel Dinkey Operator · Dinkey Driver
Related jobs
What these numbers mean
The score is the share of this job’s work, weighted by how important and frequent each task is, that AI could do in half the time: tasks an AI model could do alone count in full, tasks that need software built on AI count half.
“AI already used” is the share of the work in tasks where people are recorded using AI today. “As AI tools mature” counts every task AI could halve, with or without extra software.
The percentile compares the score with every job’s, weighted by how many people in the US do each one. Exposure means AI could change how the work is done, not that the job goes away. These are estimates for the typical job, not predictions.
Sources
- O*NET 31.0 Database, U.S. Department of Labor, Employment and Training Administration
- GPTs are GPTs: Labor market impact potential of LLMs (task labels), Eloundou, Manning, Mishkin & Rock (2023), OpenAI and University of Pennsylvania
- Anthropic Economic Index: labor market impacts (task penetration), Anthropic
- Occupational Employment and Wage Statistics, May 2025 (national and metropolitan areas), U.S. Bureau of Labor Statistics