Will AI replace Millwrights?
AI reaches little of this job’s work.
3/100
Low exposure
More exposed to AI than 10% of US workers.
- AI already used in
- 0% of the work
- As AI tools mature: up to
- 7% of the work
What the job involves
Install, dismantle, or move machinery and heavy equipment according to layout plans, blueprints, or other drawings.
Where AI reaches the work
The job’s main tasks, heaviest first, by how far AI reaches them.
Within reach(2)
- Troubleshoot equipment, electrical components, hydraulics, or other mechanical systems.
- Install robot and modify its program, using teach pendant.
Out of reach(21)
- Replace defective parts of machine, or adjust clearances and alignment of moving parts.
- Align machines or equipment, using hoists, jacks, hand tools, squares, rules, micrometers, lasers, or plumb bobs.
- Insert shims, adjust tension on nuts and bolts, or position parts, using hand tools and measuring instruments, to set specified clearances between moving and stationary parts.
- Signal crane operator to lower basic assembly units to bedplate, and align unit to centerline.
- Conduct preventative maintenance and repair, and lubricate machines and equipment.
and 16 more
Also called
Maintenance Millwright · Millwright · Machine Erector · Machinery Erector · Millwright Apprentice · Automated Equipment Engineering Technician (Automated Equipment Engineering Tech) · Automated Equipment Engineering Tech · Gear Repairer
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