Use as a copilot
Task areas where people work with AI — iterating, learning, or checking — staying in the loop rather than handing the task off.
- Wet concrete surface and rub with stone to smooth surface and obtain specified finish. · 0.4%
Terrazzo Workers and Finishers
Occupation · SOC 47-2053.00
Apply a mixture of cement, sand, pigment, or marble chips to floors, stairways, and cabinet fixtures to fashion durable and decorative surfaces.
Also called: Terrazzo Finisher · Terrazzo Installer · Terrazzo Tile Setter · Terrazzo Worker · Grinder · Installer · Terrazzo Grinder · Terrazzo Journeyman · Terrazzo Laborer · Terrazzo Mechanic · Artificial Marble Worker · Build Master
Job family: Construction and Extraction Occupations
Take this to your AI
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-47-2053-00/context.md directly.
AI work map
A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.
Keep a human in the loop
Task areas where a human was still judged necessary in a large share of observed conversations — not a safety ruling, an observed-need signal.
- Wet concrete surface and rub with stone to smooth surface and obtain specified finish. · 100.0% need a human
Skills it runs on
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Market signal
Independent published positions, read together — not a forecast.
- Declining employment outlook (-11.1% by 2034)
- 100 openings/yr
- Low AI exposure
- Observed AI use leans augmentation
- Median pay $57,260/yr
- Work is mostly on-site (not teleworkable)
- 2013 flagged this for computerization (75th); today's AI task-overlap is comparatively low (5th)
5th-percentile task overlap — yet about 100 openings a year (-11.1% projected, BLS), and observed AI use leans 5135% copilot, not hand-off (AEI) . What exposure means →
AI & job outlook
What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.
Exposure to current AI
Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.
| Measure | Rank vs all occupations | Percentile | Score |
|---|---|---|---|
| Overall AI exposure (Felten et al.) Low | 2nd | -1.8 | |
| LLM task exposure, γ (OpenAI / Eloundou) Low | 3rd | 0.0 | |
| AI assistant applicability (Microsoft) Low | 21st | 0.1 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.0), with simple added tooling (β 0.0), and including AI-powered software (γ 0.0). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.
This job mostly cannot be done remotely (Dingel–Neiman) — its hands-on tasks sit outside what software-based AI reaches.
Mixed signals. Today's AI/LLM studies show relatively low exposure for this job, but the older (2013) Frey–Osborne work rated it higher for computerization and robotics. Different eras, different technologies — the AI measures above reflect the current state.
Historical automation estimate (2013)
A pre-LLM (2013) estimate of how automatable this job is by computerization and robotics. Shown for historical context only — it is not part of any current AI ranking.
Frey–Osborne probability 0.9 · 75th percentile among occupations · High
Job outlook
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | Declining · -11.1% by 2034 |
| Projected annual openings | 100 |
| Employment 2024 → 2034 | 1,500 → 1,300 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
Where this work sits on the global GenAI gradient
The ILO's 2025 global study scores generative-AI exposure on the international ISCO-08 occupation system, not US SOC. Bridged through the published (and approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 crosswalk, this US occupation corresponds to the international occupation below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.
Terrazzo Workers and Finishers sits at the 4th percentile of 427
occupations on the global GenAI task-exposure gradient
— exposure rose from 2023 to 2025. Each dot is one occupation; the
ringed one is this work. Exposure is task overlap, not automation or jobs lost.
10% mean task exposure (2025)
4th percentile of 427 placed occupations
+1 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Concrete Placers, Concrete Finishers and Related Workers · 7114 | 10% | Not exposed |
Read the whole six-band gradient on the GenAI exposure gradient page. The crosswalk is approximate: a US occupation can map to several international ones, and the ILO scores describe the international occupation, not this exact US role.
Working with AI in this job
How people actually apply AI to this occupation's tasks, from Claude.ai (Free and Pro) conversations in the Anthropic Economic Index, 2026-01-15. This is one AI assistant's consumer sample — not all AI, not the whole workforce. Autonomy and the collaboration mix are model-rated estimates; figures below the sample floor are hidden.
| Augmentation vs. automation | 51.4% working with AI · — handed to AI |
| Most common way people use AI here | Learning · you ask AI to explain or teach |
| Typical AI autonomy | 4.0 / 5 · higher = AI acts more independently |
What people delegate to AI
The role's most common tasks in AI conversations, each tagged with how people work with the AI on it. “Usage” is the share of observed conversations, not of the job.
| Task | How | Usage |
|---|---|---|
| Wet concrete surface and rub with stone to smooth surface and obtain specified finish. | Learning | 0.4% |
Where a human is still needed
Tasks where the model most often judged that a person remained necessary — a useful read on the current boundary, not a guarantee.
| Wet concrete surface and rub with stone to smooth surface and obtain specified finish. | 100.0% |
What people most often hand AI here
Example prompts phrased from the tasks people most often delegate to AI in this occupation (Anthropic Economic Index). Each shows the underlying measured task and its share of observed AI use. They are suggested phrasings of real tasks — starting points, not endorsed instructions.
-
Help me wet concrete surface and rub with stone to smooth surface and obtain specified finish.From: Wet concrete surface and rub with stone to smooth surface and obtain specified finish. · 0.4% of measured AI use · learning
Tasks
All 26 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Measure designated amounts of ingredients for terrazzo or grout, according to standard formulas and specifications, using graduated containers and scales, and load ingredients into portable mixer. Core · importance 4.6
- Grind surfaces with a power grinder, or polish surfaces with polishing or surfacing machines. Core · importance 4.4
- Cut metal division strips and press them into the terrazzo base for joints or changes of color to form designs or patterns or to help prevent cracks. Core · importance 4.4
- Blend marble chip mixtures, place into panels, and push a roller over the surface to embed the chips. Core · importance 4.3
- Modify mixing, grouting, grinding, or cleaning procedures, according to type of installation or material used. Core · importance 4.3
- Spread, level, or smooth concrete or terrazzo mixtures to form bases or finished surfaces, using rakes, shovels, hand or power trowels, hand or power screeds, or floats. Core · importance 4.2
- Grind curved surfaces or areas inaccessible to surfacing machine, such as stairways or cabinet tops, with portable hand grinder. Core · importance 4.2
- Wash polished terrazzo surface, using cleaner and water, and apply sealer and curing agent according to manufacturer's specifications, using brush or sprayer. Core · importance 4.2
- Position and secure moisture membrane and wire mesh in preparation for pouring base materials for terrazzo installation. Core · importance 4.1
- Fill slight grinding depressions with matching grout material and hand-trowel for a smooth, uniform surface. Core · importance 4.0
- Clean installation site, mixing and storage areas, tools, machines, and equipment, and store materials and equipment. Core · importance 4.0
- Sprinkle colored marble or stone chips, powdered steel, or coloring powder over surface to produce prescribed finish. Core · importance 4.0
- Mix cement, sand, and water to produce concrete, grout, or slurry, using hoe, trowel, tamper, scraper, or concrete-mixing machine. Core · importance 4.0
- Wet surface to prepare for bonding, fill holes and cracks with grout or slurry, and smooth with a trowel. Core · importance 4.0
- Chip, scrape, or grind high spots, ridges, or rough projections to finish concrete, using pneumatic chisel, hand chisel, or other hand tools. Core · importance 3.9
- Mold expansion joints and edges, using edging tools, jointers, or straightedges. Core · importance 3.8
- Move terrazzo installation materials, tools, machines, or work devices to work areas, manually or using wheelbarrow. Core · importance 3.8
- Repair concrete by cutting out damaged areas, drilling holes for reinforcing rods, and positioning reinforcing rods, using power saw and drill. Supplemental · importance 3.6
- Clean chipped area, using wire brush, and feel and observe surface to determine if it is rough or uneven. Core · importance 3.5
- Precast terrazzo blocks in wooden forms. Supplemental · importance 3.3
- Wet concrete surface and rub with stone to smooth surface and obtain specified finish. Supplemental · importance 3.2
- Build wooden molds, clamping molds around areas to be repaired, or setting up frames to the proper depth and alignment. Supplemental · importance 3.2
- Spread roofing paper on surface of foundation and spread concrete onto roofing paper with trowel to form terrazzo base. Supplemental · importance 3.0
- Produce rough concrete surface, using broom. Supplemental · importance 2.9
- Remove frames when the foundation is dry. Supplemental · importance 2.9
- Signal truck driver to position truck to facilitate pouring concrete and move chute to direct concrete on forms. Supplemental · importance 2.8
Work activities
- Cut metal components for installation.
- Apply decorative masonry finishes.
- Mix substances or compounds needed for work activities.
- Measure materials or objects for installation or assembly.
- Load materials into construction equipment.
- Finish concrete surfaces.
- Spread concrete or other aggregate mixtures.
- Smooth surfaces with abrasive materials or tools.
- Align masonry materials.
- Plan production or operational procedures or sequences.
- Clean surfaces in preparation for work activities.
- Apply sealants or other protective coatings.
- Prepare surfaces for finishing.
- Install masonry materials.
- Apply material to fill gaps in surfaces.
- Drill holes in construction materials.
- Position structural components.
- Break up rock, asphalt, or concrete.
- Clean work sites.
- Clean equipment or facilities.
- Move construction or extraction materials to locations where they are needed.
- Position construction forms or molds.
- Build construction forms or molds.
- Pour materials into or on designated areas.
- Signal equipment operators to indicate proper equipment positioning.
- Install roofing materials.
- Dismantle equipment or temporary structures.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Knowledge
| Building and Construction | 4.0 | |
| Design | 3.6 | |
| Mathematics | 3.4 | |
| English Language | 3.3 | |
| Administration and Management | 3.2 | |
| Customer and Personal Service | 3.2 | |
| Chemistry | 3.1 | |
| Mechanical | 3.1 | |
| Public Safety and Security | 3.0 | |
| Production and Processing | 3.0 |
Abilities
| Manual Dexterity | 3.8 | |
| Multilimb Coordination | 3.5 | |
| Trunk Strength | 3.5 | |
| Near Vision | 3.5 | |
| Arm-Hand Steadiness | 3.4 | |
| Finger Dexterity | 3.3 | |
| Extent Flexibility | 3.3 | |
| Far Vision | 3.3 | |
| Problem Sensitivity | 3.1 | |
| Visualization | 3.1 | |
| Control Precision | 3.1 | |
| Static Strength | 3.1 | |
| Stamina | 3.1 | |
| Information Ordering | 3.0 | |
| Selective Attention | 3.0 | |
| Dynamic Strength | 3.0 | |
| Visual Color Discrimination | 3.0 | |
| Oral Comprehension | 2.9 | |
| Deductive Reasoning | 2.9 | |
| Perceptual Speed | 2.9 | |
| Reaction Time | 2.9 | |
| Depth Perception | 2.9 | |
| Speech Recognition | 2.9 |
Transferable skills
| Coordination | 3.0 | |
| Quality Control Analysis | 3.0 | |
| Judgment and Decision Making | 2.9 | |
| Operations Monitoring | 2.8 | |
| Operation and Control | 2.8 |
Essential skills
| Speaking | 2.9 | |
| Monitoring | 2.8 |
Skills in demand
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
Tools & technology
| Example | Category | |
|---|---|---|
| Intuit QuickBooks | Accounting software | Hot technology |
| Microsoft Excel | Spreadsheet software | Hot technology |
| Microsoft Windows | Operating system software | Hot technology |
| Construction Management Software ProEst | Analytical or scientific software | |
| CPR International GeneralCOST Estimator | Accounting software | |
| CPR Visual Estimator | Project management software | |
| On Center Quick Bid | Project management software | |
| Sapro Systems Paymee | Accounting software |
Work context
How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.
How to get in
- Job zone
- Zone 2 — Job Zone 1-2: Very Little to Some Preparation Needed
- Education
- Usually requires a high school diploma or GED, though some occupations may not.
- Typical entry-level education
- High school diploma or equivalent · BLS, the typical path — not a requirement
- Related experience
- Some occupations may need little or no previous experience; others require several months to a year of experience. For example, landscaping and groundskeeping workers might require very little training or previous experience, while agricultural equipment operators can benefit from on-the job training.
- Preparation level
- SVP (Below 6.0) — total schooling plus on-the-job experience.
What to study: Construction Trades . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Education of current workers
Share of people in this occupation at each level of education.
| High School Diploma | 69.9% | |
| Less than a High School Diploma | 14.2% | |
| Post-Secondary Certificate | 9.6% | |
| Some College Courses | 6.4% |
Interests & work styles
The interests and personal qualities O*NET associates with people who do this work.
Career interests (Holland / RIASEC)
| Realistic | 7.0 | |
| Conventional | 3.3 | |
| Artistic | 1.9 | |
| Investigative | 1.8 |
Interest areas
Work styles
| Dependability | 2.2 | |
| Attention to Detail | 2.1 | |
| Cautiousness | 1.4 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $39,360 |
| 25th percentile | $46,940 |
| Median (50th) | $57,260 |
| 75th percentile | $73,490 |
| 90th percentile | $104,510 |
| People employed | 1,450 |
Industries that employ this occupation
Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.
| Industry | Workers | National median pay |
|---|---|---|
| Construction · Sector | 1,430 | $57,140 |
Where this work is most concentrated
Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).
| Industry | Concentration | Workers |
|---|---|---|
| Construction · Sector | 18.72× | 1,430 |
Related occupations
Part of the Construction career cluster.
- Tile and Stone Setters · 47-2044.00 Compare →
- Helpers--Brickmasons, Blockmasons, Stonemasons, and Tile and Marble Setters · 47-3011.00 Compare →
- Floor Layers, Except Carpet, Wood, and Hard Tiles · 47-2042.00 Compare →
- Cement Masons and Concrete Finishers · 47-2051.00 Compare →
- Stonemasons · 47-2022.00 Compare →
- Brickmasons and Blockmasons · 47-2021.00 Compare →
- Stone Cutters and Carvers, Manufacturing · 51-9195.03 Compare →
- Floor Sanders and Finishers · 47-2043.00 Compare →
- Molders, Shapers, and Casters, Except Metal and Plastic · 51-9195.00 Compare →
- Furniture Finishers · 51-7021.00 Compare →
- Plasterers and Stucco Masons · 47-2161.00 Compare →
- Refractory Materials Repairers, Except Brickmasons · 49-9045.00 Compare →
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
What you can do with this
Options the data surfaces for Terrazzo Workers and Finishers — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Skills that travel
Capabilities this work builds that are used across many other occupations.
Adjacent roles
Occupations O*NET rates as related — the nearby moves on the map.
Paths in
How people typically prepare for this work.
- High school diploma or equivalent · typical entry level
- Job zone 2 — Job Zone 1-2: Very Little to Some Preparation Needed · preparation tier
- Construction Trades · field of study
Zoom out
On the global GenAI exposure gradient this work sits around the 4th percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Terrazzo Workers and Finishers show 5th-percentile AI task overlap — and about 100 annual U.S. openings
- Terrazzo Workers and Finishers rank in the 5th percentile (Low band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated.Eloundou et al. (GPTs are GPTs) + Felten AIOE
- The occupation is projected to see about 100 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI.BLS Employment Projections 2024–34
- BLS projects employment to be declining (-11.1%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $57,260, across about 1,450 U.S. workers.BLS OEWS (May 2024)
- Of the AI use actually observed for this work, 51% looks like augmentation (drafting, iterating, checking) rather than hands-off automation — from a Claude.ai usage sample, not a census.2026-01-15-v4-plus-2025-03-27-v2
Copy the whole kit
Terrazzo Workers and Finishers show 5th-percentile AI task overlap — and about 100 annual U.S. openings • Terrazzo Workers and Finishers rank in the 5th percentile (Low band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE) • The occupation is projected to see about 100 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34) • BLS projects employment to be declining (-11.1%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $57,260, across about 1,450 U.S. workers. (BLS OEWS (May 2024)) • Of the AI use actually observed for this work, 51% looks like augmentation (drafting, iterating, checking) rather than hands-off automation — from a Claude.ai usage sample, not a census. (2026-01-15-v4-plus-2025-03-27-v2) Source: Singulariki — "Terrazzo Workers and Finishers". https://singulariki.com/roles/role-47-2053-00 Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.
AssetsShare imageMethodology & sourcesPress & newsroomThe newsroom
Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.
Sources for this page
Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.
- O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
- BLS Occupational Employment and Wage Statistics (OEWS) May 2024 U.S. Bureau of Labor Statistics
- BLS Employment Projections 2024–2034 U.S. Bureau of Labor Statistics
- Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27) Anthropic
- Microsoft “Working with AI” working-with-ai Microsoft Research
- “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic
- AI Occupational Exposure (AIOE) Felten, Raj & Seamans academic
- ILO / Gmyrek et al. GenAI exposure gradient 2025 International Labour Organization
- IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022 Institute for Structural Research (IBS)
- Frey & Osborne (2013) frey-osborne-automation academic
- Dingel & Neiman (2020) dingel-neiman-workathome academic
Data compiled June 2, 2026. Figures are estimates, not advice.
Cite this page
Plain
Singulariki. "Terrazzo Workers and Finishers." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-47-2053-00
APA
Singulariki. (2026). Terrazzo Workers and Finishers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-47-2053-00
BibTeX
@misc{singulariki-role-47-2053-00,
title = {Terrazzo Workers and Finishers},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
url = {https://singulariki.com/roles/role-47-2053-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.