Medium AI Risk Fast Growth

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.

AI Exposure Score
29% Medium

Proportion of tasks susceptible to AI automation (O*NET analysis)

Projected Growth
+9.5%
2024–2034 (BLS)
+3,200 jobs
Median Annual Wage
$54,340
BLS May 2024
How wage figures are sourced →
The verdict

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.

29%
AI exposure
27th
percentile
+9.5%
Job growth 2024–34
$54,340
Median wage

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.

AI exposure distribution - Floor layers, except carpet, wood, and hard tiles marked 1 occupations at 0–10% 1 0 43 occupations at 10–20% 43 10 184 occupations at 20–30% 184 20 332 occupations at 30–40% 332 30 158 occupations at 40–50% 158 40 64 occupations at 50–60% 64 50 29 occupations at 60–70% 29 60 15 occupations at 70–80% 15 70 5 occupations at 80–90% 5 80 1 occupations at 90–100% 1 90 AI exposure (%) →
Top 73% by AI exposure Higher AI exposure than 27% of all 832 occupations.

Floor layers, except carpet, wood, and hard tiles has ai exposure of 29%. Distribution: 1 occupations at 0-10%; 43 occupations at 10-20%; 184 occupations at 20-30%; 332 occupations at 30-40%; 158 occupations at 40-50%; 64 occupations at 50-60%; 29 occupations at 60-70%; 15 occupations at 70-80%; 5 occupations at 80-90%; 1 occupations at 90-100%.

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.

Future-proofGrowing but exposedStable, lower-AIMost at risk11.8%18.4%25%31.6%38.2%-1.3%1.5%4.3%7.2%10.0%AI exposure (%) →Projected growth (%) →Floor layersConstruction laborerCarpentersFirst-line supervisoElectriciansPlumbersOperating engineersPaintersCement masonsRoofersHighway maintenance Construction

Source: BLS Employment Projections 2024–2034 (growth) and O*NET (AI-exposure analysis by PlainWorkforce).

Employment Projections

33,700
Employment 2024
36,900
Projected 2034
+9.5%
Change (%)
+3,200
Change (jobs)

Occupation Insight

Floor layers, except carpet, wood, and hard tiles (SOC 47-2042) carries an AI exposure score of 29%, placing it in the Medium automation-risk tier. This score is computed from O*NET Database 30.0 task-level analysis, where each task an 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 economic context matters alongside the risk score. BLS counted approximately 33,700 workers in this occupation in 2024, and projects a +9.5% change through 2034 - modest growth that keeps the occupation viable even as tasks evolve. Median annual compensation stands at $54,340, reflecting both skill scarcity and the value employers place on the tasks that remain difficult to automate. Entry typically requires No formal educational credential, plus None of related experience.

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. Pair the AI exposure score with the BLS employment projection and wage percentiles above for a complete career assessment.

Education & Entry Requirements

Typical Education
No formal educational credential
Work Experience
None
On-the-Job Training
Moderate-term on-the-job training

Top Tasks (O*NET)

  1. 1. Sweep, scrape, sand, or chip dirt and irregularities to clean base surfaces, correcting imperfections that may show through the covering.
  2. 2. Cut flooring material to fit around obstructions.
  3. 3. Inspect surface to be covered to ensure that it is firm and dry.
  4. 4. Trim excess covering materials, tack edges, and join sections of covering material to form tight joint.
  5. 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. 6. Measure and mark guidelines on surfaces or foundations, using chalk lines and dividers.
  7. 7. Cut covering and foundation materials, according to blueprints and sketches.
  8. 8. Roll and press sheet wall and floor covering into cement base to smooth and finish surface, using hand roller.
  9. 9. Apply adhesive cement to floor or wall material to join and adhere foundation material.
  10. 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

1.4
out of 5.0

Medium automation risk based on 10 analyzed tasks. Most tasks require human judgment and are resistant to automation.

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).

Data sourced from official public datasets. See our methodology for details. Retrieved and formatted by PlainWorkforce Editorial

Every figure on PlainWorkforce is rendered directly from BLS/O*NET source data, no number is typed in by an editor. See our editorial standards & corrections policy, the methodology behind these figures, or report a data error. Data current as of BLS Employment Projections 2024-2034.