Floor layers, except carpet, wood, and hard tiles
SOC Code: 47-2042
Floor layers, except carpet, wood, and hard tiles carries a 29% AI exposure score (Medium automation risk), with a median annual wage of $54,340 and +9.5% projected employment growth from 2024 to 2034 (BLS), affecting approximately 33,700 workers. Full task breakdown, skills, and employer data are below.
Proportion of tasks susceptible to AI automation (O*NET analysis)
At 29% AI exposure, Floor layers, except carpet, wood, and hard tiles sits 8 points below the 37.2% average across 832 U.S. occupations - more exposed than 27% of them. Most of its core tasks still require human judgment.
Career outlook score
70/100
Floor layers, except carpet, wood, and hard tiles, weighted across 3 of 3 tracked dimensions
A weighted composite of median wage, projected growth, and AI-automation security (inverted exposure), each benchmarked against every other tracked occupation. It describes this occupation's standing across those three dimensions, not a guarantee of future outcomes.
- Median wage D $54,340
Annual median wage, percentile rank vs all tracked occupations
- Projected growth A+ +9.5%
Projected employment change, 2024-2034, BLS Employment Projections
- AI exposure (inverted) B 29% exposure
Lower O*NET task-automability scores lower risk; this dimension scores security, not exposure
Home health and personal care aides is #1 of 832 occupations by employment (4.3M, AI exposure rank #392 at 35%) vs. Bookkeeping, accounting, and auditing clerks #1 by AI task exposure (95%, employment rank #17 at 1.6M).
Automation-risk inventory
Exclusive cut of 832 occupations by PlainWorkforce automation-risk band. Orthogonal to the continuous AI-exposure distribution chart below and to this occupation's single risk badge, this is the corpus band mix, with Floor layers, except carpet, wood, and hard tiles in the Medium band.
Credential × growth standing
Open entry with non-declining BLS pace
Floor layers, except carpet, wood, and hard tiles keeps an No credential bar (109 of 832) and sits in Fast growth (67 of 832). Lower formal gates with a non-shrinking employment line - skill and AI desks matter more than credentials here.
Where Floor layers, except carpet, wood, and hard tiles sits among all occupations
AI-exposure score distribution across 832 U.S. occupations (O*NET task analysis). This occupation is marked in rose.
Where Floor layers, except carpet, wood, and hard tiles sits by AI exposure
AI-exposure score distribution across U.S. occupations (O*NET task analysis)
29% Lower than most lower than 73% of 832 occupations
Occupations, banded by AI-exposure score
Each bar is a band; taller bars hold more occupations. The dashed line + filled bar mark this entry. Hover or tap any bar for its full count and share, and where it sits relative to this entry.
Source O*NET task data (U.S. Department of Labor) · BLS 2024–2034
Source: O*NET task data (U.S. Department of Labor); AI-exposure scores are PlainWorkforce's analysis. As of BLS 2024–2034.
Floor layers, except carpet, wood, and hard tiles vs. its occupational neighbors
AI exposure (horizontal) vs projected 2024–2034 growth (vertical) for occupations in the same SOC group. Floor layers, except carpet, wood, and hard tiles is marked in rose; the top-left corner is the most future-proof.
Source: BLS Employment Projections 2024–2034 (growth) and O*NET (AI-exposure analysis by PlainWorkforce).
Employment Projections
Where This Score Comes From
Floor layers, except carpet, wood, and hard tiles's Medium automation-risk tier is computed from O*NET Database 30.0 task-level analysis, where each documented task the occupation performs is evaluated against current generative AI, robotic process automation, and machine-learning capabilities. A score below 40% reflects tasks anchored in physical dexterity, unstructured environments, or high-touch human interaction that current AI cannot reliably replicate.
The employment, wage, and education figures above come from a second, separate federal source: BLS Employment Projections 2024–2034, matched to the O*NET task data by Standard Occupational Classification (SOC 47-2042) code, with the wage figure cross-validated against the BLS Occupational Employment and Wage Statistics (OEWS) May 2024 survey. BLS figures are presented exactly as published, with no adjustment on our part; the SOC-code match is what lets Floor layers, except carpet, wood, and hard tiles be compared directly against every other tracked occupation on the same basis, not just roles that happen to share a job title.
For career planners, this profile should be read alongside the task, skill, and knowledge breakdowns below and the list of employers whose workforce composition includes Floor layers, except carpet, wood, and hard tiles. Adjacent occupations shown further down offer lateral moves that preserve industry knowledge while potentially reducing exposure.
Education & Entry Requirements
Top Tasks (O*NET)
- 1. Sweep, scrape, sand, or chip dirt and irregularities to clean base surfaces, correcting imperfections that may show through the covering.
- 2. Cut flooring material to fit around obstructions.
- 3. Inspect surface to be covered to ensure that it is firm and dry.
- 4. Trim excess covering materials, tack edges, and join sections of covering material to form tight joint.
- 5. Form a smooth foundation by stapling plywood or Masonite over the floor or by brushing waterproof compound onto surface and filling cracks with plaster, putty, or grout to seal pores.
- 6. Measure and mark guidelines on surfaces or foundations, using chalk lines and dividers.
- 7. Cut covering and foundation materials, according to blueprints and sketches.
- 8. Roll and press sheet wall and floor covering into cement base to smooth and finish surface, using hand roller.
- 9. Apply adhesive cement to floor or wall material to join and adhere foundation material.
- 10. Determine traffic areas and decide location of seams.
Key Skills Required
- Active Listening
- Speaking
- Critical Thinking
- Monitoring
- Social Perceptiveness
- Coordination
- Judgment and Decision Making
- Time Management
- Active Learning
- Complex Problem Solving
Knowledge Areas
- Building and Construction
- Customer and Personal Service
- Mathematics
- Mechanical
- Production and Processing
- Design
- English Language
- Education and Training
- Public Safety and Security
- Transportation
Frequently Asked Questions
Will AI replace Floor layers, except carpet, wood, and hard tiles?
Floor layers, except carpet, wood, and hard tiles has an AI exposure score of 29%, indicating a medium level of automation risk. The majority of tasks in this role require human judgment, creativity, or physical presence that AI cannot easily replicate.
What is the job outlook for Floor layers, except carpet, wood, and hard tiles?
According to BLS Employment Projections 2024-2034, Floor layers, except carpet, wood, and hard tiles is projected to grow by 9.5% over the decade. Current employment stands at approximately 33,700 workers.
What skills are needed for Floor layers, except carpet, wood, and hard tiles?
Key skills for Floor layers, except carpet, wood, and hard tiles include Active Listening, Speaking, Critical Thinking, and others. Typical entry-level education is No formal educational credential.
How much do Floor layers, except carpet, wood, and hard tiles earn?
The median annual wage for Floor layers, except carpet, wood, and hard tiles is $54,340, according to BLS Occupational Employment and Wage Statistics (May 2024). Actual earnings vary by location, experience, industry, and employer. The BLS publishes detailed wage percentiles by region in its Occupational Employment and Wage Statistics program.
What education is required for Floor layers, except carpet, wood, and hard tiles?
The typical entry-level education for Floor layers, except carpet, wood, and hard tiles is No formal educational credential. Employers generally expect None of related work experience. On-the-job training typically involves Moderate-term on-the-job training. Requirements can vary by employer and specialization.
Which companies employ Floor layers, except carpet, wood, and hard tiles?
Floor layers, except carpet, wood, and hard tiles roles exist across many industries and employers. Workforce composition is estimated from BLS industry-occupation employment distributions matched to SEC-registered public companies.
AI Exposure Rating
Medium automation risk based on 10 analyzed tasks. Most tasks require human judgment and are resistant to automation.
Nationwide occupations with similar workforce profiles
Two data-derived peer sets for Floor layers, except carpet, wood, and hard tiles: AI-exposure neighbors and BLS 2034 growth neighbors (distinct comparison neighborhoods, cross-occupation).
Similar AI exposure score
Nearest O*NET task-automability scores nationwide (29% here).
- Anesthesiologists · AI exposure 29%
- Cooks, short order · AI exposure 29%
- Elevator and escalator installers and repairers · AI exposure 29%
- Fence erectors · AI exposure 29%
Similar projected growth (2024–2034)
Nearest BLS employment change rates nationwide (+9.5% here).
- Audiologists · growth +9.5%
- Chiropractors · growth +9.5%
- Electricians · growth +9.5%
- Exercise physiologists · growth +9.5%
Peers are nearest-neighbor matches on published BLS + O*NET metrics among occupations with ≥10,000 workers in 2024; corpus ranks above sort the full tracked set.
Related Occupations
Showing 6 of 43 occupations with a comparable automation-risk profile.
What to do with this
Use Floor layers, except carpet, wood, and hard tiles' numbers above to compare, not just read in isolation.
- Compare Floor layers, except carpet, wood, and hard tiles side by side against another occupation on wage, growth, and AI exposure. Workforce comparison tool
- Understand how the AI exposure score above is actually calculated before treating it as a verdict. Reading AI exposure scores
- See the full ranked list of occupations with the lowest automation exposure nationwide. Safest occupations from AI
AI exposure scores estimate task automatability from O*NET data; they are not a certainty of job loss, and BLS growth projections are estimates, not guarantees.
Data sources: Bureau of Labor Statistics Employment Projections 2024–2034 and O*NET Database 30.0. Employment figures are rounded. Wage data from BLS Occupational Employment Statistics (OES).