Will AI replace Paving, Surfacing, and Tamping Equipment Operators?
AI reaches little of this job’s work.
0/100
Low exposure
More exposed to AI than 2% of US workers.
- AI already used in
- 0% of the work
- As AI tools mature: up to
- 0% of the work
What the job involves
Operate equipment used for applying concrete, asphalt, or other materials to road beds, parking lots, or airport runways and taxiways or for tamping gravel, dirt, or other materials. Includes concrete and asphalt paving machine operators, form tampers, tamping machine operators, and stone spreader operators.
Where AI reaches the work
The job’s main tasks, heaviest first, by how far AI reaches them.
Out of reach(20)
- Start machine, engage clutch, and push and move levers to guide machine along forms or guidelines and to control the operation of machine attachments.
- Inspect, clean, maintain, and repair equipment, using mechanics' hand tools, or report malfunctions to supervisors.
- Fill tanks, hoppers, or machines with paving materials.
- Observe distribution of paving material to adjust machine settings or material flow, and indicate low spots for workers to add material.
- Operate machines to spread, smooth, level, or steel-reinforce stone, concrete, or asphalt on road beds.
and 15 more
Also called
Asphalt Paving Machine Operator · Asphalt Roller Operator · Paver Operator · Roller Operator · Screed Operator · Asphalt Paver Operator · Asphalt Distributor Tender · Asphalt Screed Operator
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