Will AI replace Tile and Stone Setters?
AI reaches little of this job’s work.
4/100
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
Apply hard tile, stone, and comparable materials to walls, floors, ceilings, countertops, and roof decks.
Where AI reaches the work
The job’s main tasks, heaviest first, by how far AI reaches them.
Within reach(2)
- Determine and implement the best layout to achieve a desired pattern.
- Prepare cost and labor estimates, based on calculations of time and materials needed for project.
Out of reach(23)
- Align and straighten tile using levels, squares, and straightedges.
- Finish and dress the joints and wipe excess grout from between tiles, using damp sponge.
- Cut and shape tile to fit around obstacles and into odd spaces and corners, using hand and power cutting tools.
- Lay and set mosaic tiles to create decorative wall, mural, and floor designs.
- Mix, apply, and spread plaster, concrete, mortar, cement, mastic, glue or other adhesives to form a bed for the tiles, using brush, trowel and screed.
and 18 more
Also called
Tile Installer · Ceramic Tile Mechanic · Tile Mason · Tile Setter · Acoustical Installer · Acoustical Carpenter · Acoustical Material Worker · Ceramic Tile Installer
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