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Tapers

Occupation · SOC 47-2082.00

Seal joints between plasterboard or other wallboard to prepare wall surface for painting or papering.

Also called: Drywall Finisher · Drywall Taper · Finisher · Taper · Drywall Mechanic · Sheet Rock Taper · Spackler · Wall Taper

Job family: Construction and Extraction Occupations

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A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch /roles/role-47-2082-00/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.

3rd-percentile task overlap — yet about 1,100 openings a year (+0.1% projected, BLS) . 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 5th -1.5
LLM task exposure, γ (OpenAI / Eloundou) Low 3rd 0.0
AI assistant applicability (Microsoft) Low 10th 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.

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 0.6 · 53rd percentile among occupations · Moderate

Job outlook

Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.

Outlook About average · +0.1% by 2034
Projected annual openings 1,100
Employment 2024 → 2034 15,600 → 15,600

“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.

11% mean task exposure (2025)
6th percentile of 427 placed occupations
−1 pts shift 2023 → 2025
International occupation (ISCO-08) Task exposure (2025) Most tasks fall in
Plasterers · 7123 11% 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.

Tasks

All 16 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.

Work activities

Knowledge, skills & abilities

O*NET importance rating, from 1 (not important) to 5 (extremely important).

Knowledge

Building and Construction 4.0
English Language 2.6
Education and Training 2.5
Customer and Personal Service 2.5
Mechanical 2.4
Administration and Management 2.4

Abilities

Near Vision 3.4
Arm-Hand Steadiness 3.1
Manual Dexterity 3.1
Multilimb Coordination 3.1
Trunk Strength 3.1
Extent Flexibility 3.1
Oral Comprehension 3.0
Oral Expression 2.9
Finger Dexterity 2.9
Control Precision 2.9
Speech Recognition 2.9
Speech Clarity 2.9
Problem Sensitivity 2.8
Deductive Reasoning 2.8
Inductive Reasoning 2.8
Information Ordering 2.8
Category Flexibility 2.8
Stamina 2.8
Selective Attention 2.6
Gross Body Equilibrium 2.6
Written Comprehension 2.5
Gross Body Coordination 2.5
Far Vision 2.5
Visualization 2.4
Static Strength 2.4
Visual Color Discrimination 2.4

Essential skills

Active Listening 2.9
Speaking 2.9
Monitoring 2.9
Critical Thinking 2.6

Transferable skills

Time Management 2.8
Social Perceptiveness 2.6
Coordination 2.5
Judgment and Decision Making 2.4

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 Office software Office suite software Hot technology
Applied Computer Systems JOBPOWER Accounting software
Construction Software Center EasyEst Project management software
DevWave Estimate Works Project management software
Microsoft Dynamics Enterprise resource planning ERP software
On Center Quick Bid Project management software
Turtle Creek Software Goldenseal 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.

Spend Time Standing 4.8
Spend Time Using Your Hands to Handle, Control, or Feel Objects, Tools, or Controls 4.7
Face-to-Face Discussions with Individuals and Within Teams 4.5
Spend Time Making Repetitive Motions 4.2
Exposed to Contaminants 4.1
Wear Common Protective or Safety Equipment such as Safety Shoes, Glasses, Gloves, Hearing Protection, Hard Hats, or Life Jackets 4.1
Freedom to Make Decisions 4.0
Determine Tasks, Priorities and Goals 3.9
Time Pressure 3.9
Work With or Contribute to a Work Group or Team 3.8
Spend Time Walking or Running 3.8
Health and Safety of Other Workers 3.7
Exposed to High Places 3.7
Exposed to Sounds, Noise Levels that are Distracting or Uncomfortable 3.7
Importance of Being Exact or Accurate 3.7
Telephone Conversations 3.7
Indoors, Not Environmentally Controlled 3.6
Spend Time Bending or Twisting Your Body 3.6
Frequency of Decision Making 3.6
Impact of Decisions on Co-workers or Company Results 3.4
Contact With Others 3.3
Exposed to Cramped Work Space, Awkward Positions 3.3
Work Outcomes and Results of Other Workers 3.3
Exposed to Extremely Bright or Inadequate Lighting Conditions 3.3
Level of Competition 3.3
Exposed to Very Hot or Cold Temperatures 3.2
Spend Time Climbing Ladders, Scaffolds, or Poles 3.2
Physical Proximity 3.2
Coordinate or Lead Others in Accomplishing Work Activities 3.1
Spend Time Kneeling, Crouching, Stooping, or Crawling 2.9
In an Enclosed Vehicle or Operate Enclosed Equipment 2.8
Exposed to Minor Burns, Cuts, Bites, or Stings 2.8
Wear Specialized Protective or Safety Equipment such as Breathing Apparatus, Safety Harness, Full Protection Suits, or Radiation Protection 2.7
Exposed to Hazardous Equipment 2.5
Spend Time Keeping or Regaining Balance 2.5
Conflict Situations 2.5
Indoors, Environmentally Controlled 2.4
Importance of Repeating Same Tasks 2.4
Outdoors, Under Cover 2.3
Written Letters and Memos 2.3

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
No formal educational credential · 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.

Education of current workers

Share of people in this occupation at each level of education.

High School Diploma 45.7%
Less than a High School Diploma 29.0%
Post-Secondary Certificate 25.3%

Interests & work styles

The interests and personal qualities O*NET associates with people who do this work.

Career interests (Holland / RIASEC)

Realistic 6.5
Conventional 3.4
Artistic 1.7
Investigative 1.6
Social 1.4
Enterprising 1.1

Interest areas

Physical/Manual Labor 5.9
Construction/Woodwork 3.0
Mechanics/Electronics 1.4
Engineering 1.4
Transportation/Machine Operation 1.2
Applied Arts and Design 1.2
Visual Arts 1.1
Accounting 1.1

Work styles

Attention to Detail 2.3
Dependability 2.0

Wages & employment

U.S. · annual wages (BLS OEWS)

$43k10th$51k25th$65kMedian$83k75th$106k90th
Annual wages by percentile — U.S. (BLS OEWS). The light band spans the 10th–90th percentile; the darker band is the middle half (25th–75th); the line is the median.
16k202416k2034 (proj.)+0.1% · About average
Projected U.S. employment, 2024–2034 (BLS Employment Projections). A labor-market forecast for the occupation, not an AI-impact forecast.
10th percentile $43,450
25th percentile $50,780
Median (50th) $64,700
75th percentile $82,990
90th percentile $106,160
People employed 12,500

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 12,390 $64,840
Drywall and Insulation Contractors · National industry 9,780 $63,940
Painting and Wall Covering Contractors · National industry 620 $46,400
Manufacturing · Sector 70 $46,300
Masonry Contractors · National industry — $63,060

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
Drywall and Insulation Contractors · National industry 491.03× 9,780
Painting and Wall Covering Contractors · National industry 37× 620
Construction · Sector 18.82× 12,390

Part of the Construction career cluster.

Exposure quadrant: AI task-overlap percentile vs Median pay Tapers sits at the 3rd percentile of AI task-overlap and the 54th percentile of median pay, placed here against 12 adjacent occupations on the same two axes. Lower overlap · higher pay Higher overlap · higher pay Higher overlap · lower pay Lower overlap · lower pay Tapers Cement Masons and Concrete Finishers Roofers Construction Laborers Drywall and Ceiling Tile Installers Insulation Workers, Floor, Ceiling, and Wall Brickmasons and Blockmasons AI task-overlap percentile → ↑ Median pay
AI task-overlap percentile (horizontal) vs. median-pay percentile (vertical), across all scored occupations. This occupation is highlighted; related occupations are plotted alongside it. Overlap measures shared tasks with AI, not automation.

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 Tapers — 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.

Zoom out

On the global GenAI exposure gradient this work sits around the 6th percentile of 427 international occupations.

Write a report on thisheadline · factoids · citation

Tapers show 3rd-percentile AI task overlap — and about 1,100 annual U.S. openings

  • Tapers rank in the 3rd 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 1,100 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 about average (+0.1%) from 2024 to 2034.BLS Employment Projections 2024–34
  • Median annual pay is $64,700, across about 12,500 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Tapers show 3rd-percentile AI task overlap — and about 1,100 annual U.S. openings

• Tapers rank in the 3rd 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 1,100 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 about average (+0.1%) from 2024 to 2034. (BLS Employment Projections 2024–34)
• Median annual pay is $64,700, across about 12,500 U.S. workers. (BLS OEWS (May 2024))

Source: Singulariki — "Tapers". https://singulariki.com/roles/role-47-2082-00
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.

Data compiled June 2, 2026. Figures are estimates, not advice.

Cite this page
Plain

Singulariki. "Tapers." 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; 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-47-2082-00

APA

Singulariki. (2026). Tapers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-47-2082-00

BibTeX 
@misc{singulariki-role-47-2082-00,
  title  = {Tapers},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; 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-47-2082-00}
}

Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.

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