Share and intensity of work current AI systems can materially affect.
SOC 47-2044
Tile and Stone Setters AI displacement risk
Tile and stone setters cut, lay, and grout tile in bathrooms, kitchens, and lobbies. Layout software plans patterns and cuts, but substrate judgment, waterproofing, and fitting tile around the irregular reality of actual rooms keep this a handcraft trade.
Likely potential for exposed tasks to move to software after workflow integration.
Remodeling demand drives the trade, and failed waterproofing is the industry's expensive lesson: setters who own shower systems and large-format techniques command premium rates. No robot fits tile around a real plumbing stack.
Distribution
Where Tile and Stone Setters sits across 620 tracked roles
Displacement pressure 14 — higher than 8% of the 620 occupations tracked on displacement.ai.
Score version
This page uses Seed model v0.4 (seed-v0.4-2026-05), last reviewed 2026-08-15. Directional occupation-level planning model using hand-reviewed public research, task exposure estimates, wage context, and transition-pathway assumptions.
25 O*NET task statements matched to SOC 47-2044. The displayed task profile combines these official task statements with the current public score model.
Median wage context: $55,690 (May 2025, US national). The latest BLS row matched SOC 47-2044.
Scores are planning signals, not forecasts. Local hiring demand, employer-specific workflows, licensing, and credentials must be validated before making career decisions.
2030 economic stress test
How Anthropic's scenarios classify Tile and Stone Setters
SOC 47-2044 places this role in the paper's all-other occupation group. These group-level outcomes do not change the 14/100 role score and are not an occupation forecast.
+1.1% group wage
Employment rises and unemployment falls for the all-other group, but the paper does not publish a separate group rate.
Economy-wide: +1.6% GDP and 3.9% unemployment.
+5.9% group wage
Employment rises and unemployment falls for the all-other group, but the paper does not publish a separate group rate.
Economy-wide: +8.3% GDP and 4.6% unemployment.
+33.6% group wage
Employment rises and unemployment falls for the all-other group, but the paper does not publish a separate group rate.
Economy-wide: +32.4% GDP and 11.9% unemployment.
Compare the assumptions and limitations across all three scenarios. Source: The Anthropic Institute Working Paper No. 2026-02.
Official task evidence
O*NET task matches for Tile and Stone Setters
The current evidence import matched 25 task statements from Task Statements 31.0 (August 2026). These rows are used as a grounding layer for judging which parts of the occupation are repeatable, language-heavy, analytical, social, physical, or compliance-sensitive.
Dataset31.0 (August 2026)
Matched tasks25
SOC47-2044
- Core task / ID 2848
Align and straighten tile using levels, squares, and straightedges.
- Core task / ID 2851
Finish and dress the joints and wipe excess grout from between tiles, using damp sponge.
- Core task / ID 2850
Cut and shape tile to fit around obstacles and into odd spaces and corners, using hand and power cutting tools.
- Core task / ID 2849
Determine and implement the best layout to achieve a desired pattern.
- Core task / ID 2853
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.
- Core task / ID 2859
Study blueprints and examine surface to be covered to determine amount of material needed.
Source: O*NET Resource Center, Task Statements. Raw import target: data/raw/onet/task-statements-31-0.txt.
Task profile
Where AI changes the work
Cut and shape tile to fit obstacles and corners
Exposure 18, automation 7%, augmentation 34%.
O*NET evidence: Cut and shape tile to fit around obstacles and into odd spaces and corners, using hand ... (ID 2850)
Determine and implement the best layout pattern
Exposure 36, automation 17%, augmentation 48%.
O*NET evidence: Determine and implement the best layout to achieve a desired pattern. (ID 2849)
Mix and spread mortar to form tile beds
Exposure 16, automation 6%, augmentation 30%.
O*NET evidence: Mix, apply, and spread plaster, concrete, mortar, cement, mastic, glue or other adhesiv... (ID 2853)
Measure and mark surfaces following blueprints
Exposure 34, automation 15%, augmentation 46%.
O*NET evidence: Measure and mark surfaces to be tiled, following blueprints. (ID 2855)
TaskExposureAutomationAugmentation
Cut and shape tile to fit obstacles and corners187%34%
Determine and implement the best layout pattern3617%48%
Mix and spread mortar to form tile beds166%30%
Measure and mark surfaces following blueprints3415%46%
Transition pathways
Adjacent moves that preserve existing skills
credentialed transition
LowTile Contractor
Training horizon: 12-24 months. Skill overlap 64. Wage preservation signal 134.
- Earn contractor licensing
- Bid bathroom and kitchen remodels
- Build a crew
role redesign
LowStone Fabrication Specialist
Training horizon: 6-12 months. Skill overlap 60. Wage preservation signal 112.
- Learn CNC saw operation
- Master slab layout
- Serve countertop shops
Comparison guides
Compare the next move before you commit
12-24 months
Tile and Stone Setters to Tile Contractor
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Tile and Stone Setters into Tile Contractor.
6-12 months
Tile and Stone Setters to Stone Fabrication Specialist
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Tile and Stone Setters into Stone Fabrication Specialist.
What the AI risk score means for Tile and Stone Setters
The displacement pressure score for Tile and Stone Setters is 14. That score blends task exposure, automation pressure, augmentation potential, wage vulnerability, transition feasibility, and source confidence. It is designed to help workers and workforce teams decide where to act first, not to claim a specific date when a job will disappear.
For this role, the clearest risk pattern is visible at the task level. Determine and implement the best layout pattern carries 17% automation pressure, while Determine and implement the best layout pattern carries 48% augmentation potential. That means the best response is usually a targeted redesign of work: move away from repeatable production tasks and toward judgment, exception handling, coordination, stakeholder context, and accountable use of AI tools.
Labor-market context and wage risk
Median wage: $55,690 (May 2025, US national). Employment context: Finish trade where layout precision meets wet rooms. Typical education: High school plus apprenticeship.
Wage vulnerability is 40, while transition feasibility is 58. A high wage-vulnerability score means workers should pay close attention to salary preservation before making a move. A high transition-feasibility score means there are adjacent paths that can reuse existing skills without requiring a complete career reset.
- Low displacement pressure
- Remodel demand drives the trade
- Irregular rooms resist automation
Upskilling priorities
Skills that make this role more resilient
The safest upskilling plan starts with skills already close to the work. For Tile and Stone Setters, the strongest near-term skill priorities are listed below. These are useful whether the goal is to stay in the role, move to a redesigned version of the role, or transition into an adjacent occupation.
Tile craftsmanship
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Layout planning
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Waterproofing technique
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Blueprint reading
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
90-day transition plan
The most practical next step is not to wait for a layoff or a full role redesign. Use the next 90 days to create evidence that you can operate in a safer, more AI-augmented version of the work.
- In the first 30 days, document the repetitive tasks in your current work and identify where AI can reduce drafting, lookup, classification, or reporting time.
- By 60 days, complete one small project connected to Tile Contractor, such as earn contractor licensing.
- By 90 days, compare internal openings and external postings for Tile Contractor or Stone Fabrication Specialist and update your resume around measurable workflow outcomes.
FAQ
Questions about AI and Tile and Stone Setters
Will AI replace Tile and Stone Setters?
Tile and stone setters cut, lay, and grout tile in bathrooms, kitchens, and lobbies. Layout software plans patterns and cuts, but substrate judgment, waterproofing, and fitting tile around the irregular reality of actual rooms keep this a handcraft trade. The better planning signal is not full replacement, but which tasks become automated, which tasks become AI-assisted, and which responsibilities still need human judgment.
Which parts of Tile and Stone Setters work are most exposed to AI?
Determine and implement the best layout pattern and Measure and mark surfaces following blueprints show the strongest automation pressure in this model. Determine and implement the best layout pattern and Measure and mark surfaces following blueprints are better treated as AI-augmented work.
What should Tile and Stone Setters learn next?
Start with Tile craftsmanship, Layout planning, Waterproofing technique. The most practical adjacent paths in this model are Tile Contractor and Stone Fabrication Specialist.
How should this score be used?
Use it as a planning signal, not a prediction. Confirm local hiring demand, wages, licensing, credentials, and employer adoption before making a career move.
Sources
Evidence trail
OECD / 11 July 2023OECD Employment Outlook 2023: Artificial Intelligence and the Labour MarketO*NET Resource Center / Database 31.0 (August 2026)Occupation, Task, Skill, and Work-Activity DataUS Bureau of Labor Statistics / May 2025 estimates (released 15 May 2026)Occupational Employment and Wage Statistics