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Aircraft Structure, Surfaces, Rigging, and Systems Assemblers

Occupation · SOC 51-2011.00

Assemble, fit, fasten, and install parts of airplanes, space vehicles, or missiles, such as tails, wings, fuselage, bulkheads, stabilizers, landing gear, rigging and control equipment, or heating and ventilating systems.

Also called: Assembler · Sheet Metal Assembler and Riveter (SMAR) · Sheet Metal Mechanic · Structures Technician · A&P Technician (Airframe and Powerplant Technician) · Aircraft Line Assembler · Assembly Riveter · Helicopter Technician · Structures Mechanic · Aerospace Assembler · Aircraft De-Icer Installer · Aircraft Fuselage Framer

Job family: Production Occupations

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Download .md

A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch /roles/role-51-2011-00/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.

10th-percentile task overlap — yet about 2,800 openings a year (-14.5% 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 23rd -0.9
LLM task exposure, γ (OpenAI / Eloundou) Low 7th 0.1
AI assistant applicability (Microsoft) Low 12th 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 0.1). 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 0.8 · 64th percentile among occupations · Moderate

How AI is actually used in this job

Among measured AI assistant conversations mapped to this occupation (Anthropic Economic Index, 2026-01-15), these task types came up most. These are shares of observed AI conversations — not shares of the job, of worker time, or of what could be automated.

Read blueprints, illustrations, or specifications to determine layouts, sequences of operations, or identities or relationships of parts. 0.2%

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 · -14.5% by 2034
Projected annual openings 2,800
Employment 2024 → 2034 33,600 → 28,700

“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.

27% mean task exposure (2025)
49th percentile of 427 placed occupations
−4 pts shift 2023 → 2025
International occupation (ISCO-08) Task exposure (2025) Most tasks fall in
Mechanical Machinery Assemblers · 8211 27% Minimal

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 30 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).

Abilities

Problem Sensitivity 3.8
Near Vision 3.6
Finger Dexterity 3.5
Information Ordering 3.4
Visualization 3.4
Manual Dexterity 3.4
Oral Comprehension 3.1
Written Comprehension 3.1
Deductive Reasoning 3.1
Arm-Hand Steadiness 3.1
Control Precision 3.1
Extent Flexibility 3.1
Speech Recognition 3.1
Oral Expression 3.0
Inductive Reasoning 3.0
Category Flexibility 3.0
Perceptual Speed 3.0
Selective Attention 3.0
Multilimb Coordination 3.0
Auditory Attention 3.0
Speech Clarity 3.0

Knowledge

Mathematics 3.5
Education and Training 3.5
Mechanical 3.4
English Language 3.4
Production and Processing 3.4
Design 3.4
Computers and Electronics 3.1
Public Safety and Security 3.0
Engineering and Technology 3.0

Transferable skills

Quality Control Analysis 3.4
Complex Problem Solving 3.0
Equipment Maintenance 3.0
Judgment and Decision Making 3.0
Time Management 3.0

Essential skills

Active Listening 3.1
Critical Thinking 3.1
Monitoring 3.1
Reading Comprehension 3.0
Speaking 3.0

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
Microsoft Excel Spreadsheet software Hot technology
Microsoft Office software Office suite software Hot technology
Microsoft Outlook Electronic mail software Hot technology
Microsoft Word Word processing software Hot technology
SAP software Enterprise resource planning ERP software Hot technology
Electrical power management system software Industrial control 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.

Wear Common Protective or Safety Equipment such as Safety Shoes, Glasses, Gloves, Hearing Protection, Hard Hats, or Life Jackets 5.0
Spend Time Using Your Hands to Handle, Control, or Feel Objects, Tools, or Controls 4.9
Face-to-Face Discussions with Individuals and Within Teams 4.8
Exposed to Contaminants 4.7
Importance of Being Exact or Accurate 4.5
Exposed to Hazardous Conditions 4.1
Indoors, Environmentally Controlled 4.1
Work With or Contribute to a Work Group or Team 4.1
Exposed to Sounds, Noise Levels that are Distracting or Uncomfortable 4.0
Contact With Others 4.0
Spend Time Making Repetitive Motions 4.0
Determine Tasks, Priorities and Goals 3.8
Spend Time Standing 3.7
Importance of Repeating Same Tasks 3.6
Impact of Decisions on Co-workers or Company Results 3.6
Freedom to Make Decisions 3.6
Time Pressure 3.5
Consequence of Error 3.5
Exposed to Hazardous Equipment 3.4
Health and Safety of Other Workers 3.4
Physical Proximity 3.4
Frequency of Decision Making 3.2
Spend Time Bending or Twisting Your Body 3.2
Work Outcomes and Results of Other Workers 3.2
Exposed to Minor Burns, Cuts, Bites, or Stings 3.1
Coordinate or Lead Others in Accomplishing Work Activities 3.0
Spend Time Walking or Running 2.9
Wear Specialized Protective or Safety Equipment such as Breathing Apparatus, Safety Harness, Full Protection Suits, or Radiation Protection 2.6
Level of Competition 2.6
Indoors, Not Environmentally Controlled 2.5
Spend Time Sitting 2.5
Conflict Situations 2.5
Exposed to Cramped Work Space, Awkward Positions 2.4
Pace Determined by Speed of Equipment 2.4
Deal With External Customers or the Public in General 2.3
Dealing With Unpleasant, Angry, or Discourteous People 2.3
Spend Time Kneeling, Crouching, Stooping, or Crawling 2.3
Telephone Conversations 2.2
Degree of Automation 2.2
Exposed to Very Hot or Cold Temperatures 2.0

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: Mechanic and Repair Technologies/Technicians . 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 54.8%
Post-Secondary Certificate 15.7%
Bachelor's Degree 15.7%
Associate's Degree (or other 2-year degree) 10.0%
Less than a High School Diploma 3.2%
Some College Courses 0.6%

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 3.8
Investigative 2.7
Artistic 1.7

Interest areas

Physical/Manual Labor 5.7
Mechanics/Electronics 5.5
Engineering 5.0
Construction/Woodwork 2.1
Transportation/Machine Operation 1.7
Mathematics/Statistics 1.6
Information Technology 1.5

Work styles

Dependability 4.0
Attention to Detail 3.0
Cautiousness 2.6
Integrity 2.1
Perseverance 1.5

Wages & employment

U.S. · annual wages (BLS OEWS)

$46k10th$53k25th$62kMedian$75k75th$95k90th
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.
34k202429k2034 (proj.)-14.5% · Declining
Projected U.S. employment, 2024–2034 (BLS Employment Projections). A labor-market forecast for the occupation, not an AI-impact forecast.
10th percentile $46,040
25th percentile $53,180
Median (50th) $61,680
75th percentile $75,240
90th percentile $94,950
People employed 32,890

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
Manufacturing · Sector 30,040 $61,680
Transportation and Warehousing · Sector 1,250 $61,620
Administrative and Support and Waste Management and Remediation Services · Sector 980 $43,620
Temporary Help Services · National industry 980 $43,620
Professional, Scientific, and Technical Services · Sector 440 $73,480
Engineering Services · National industry 430 $73,480
Educational Services · Sector 90 $49,750

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
Manufacturing · Sector 11.03× 30,040
Engineering Services · National industry 1.74× 430
Temporary Help Services · National industry 1.73× 980
Transportation and Warehousing · Sector 0.79× 1,250
Administrative and Support and Waste Management and Remediation Services · Sector 0.51× 980
Professional, Scientific, and Technical Services · Sector 0.19× 440

Part of the Supply Chain & Transportation career cluster.

Exposure quadrant: AI task-overlap percentile vs Median pay Aircraft Structure, Surfaces, Rigging, and Systems Assemblers sits at the 10th percentile of AI task-overlap and the 49th percentile of median pay, placed here against 10 adjacent occupations on the same two axes. Lower overlap · higher pay Higher overlap · higher pay Higher overlap · lower pay Lower overlap · lower pay Aircraft Structure, Surfaces, Rigging, and Systems Assemblers Structural Metal Fabricators and Fitters Millwrights Welding, Soldering, and Brazing Machine Setters, Operators, and Tenders Aircraft Mechanics and Service Technicians Engine and Other Machine Assemblers 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 Aircraft Structure, Surfaces, Rigging, and Systems Assemblers — 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.

Paths in

How people typically prepare for this work.

Zoom out

On the global GenAI exposure gradient this work sits around the 49th percentile of 427 international occupations.

Write a report on thisheadline · factoids · citation

Aircraft Structure, Surfaces, Rigging, and Systems Assemblers show 10th-percentile AI task overlap — and about 2,800 annual U.S. openings

  • Aircraft Structure, Surfaces, Rigging, and Systems Assemblers rank in the 10th 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 2,800 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 (-14.5%) from 2024 to 2034.BLS Employment Projections 2024–34
  • Median annual pay is $61,680, across about 32,890 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Aircraft Structure, Surfaces, Rigging, and Systems Assemblers show 10th-percentile AI task overlap — and about 2,800 annual U.S. openings

• Aircraft Structure, Surfaces, Rigging, and Systems Assemblers rank in the 10th 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 2,800 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 (-14.5%) from 2024 to 2034. (BLS Employment Projections 2024–34)
• Median annual pay is $61,680, across about 32,890 U.S. workers. (BLS OEWS (May 2024))

Source: Singulariki — "Aircraft Structure, Surfaces, Rigging, and Systems Assemblers". https://singulariki.com/roles/role-51-2011-00
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. "Aircraft Structure, Surfaces, Rigging, and Systems Assemblers." 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-51-2011-00

APA

Singulariki. (2026). Aircraft Structure, Surfaces, Rigging, and Systems Assemblers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-51-2011-00

BibTeX
@misc{singulariki-role-51-2011-00,
  title  = {Aircraft Structure, Surfaces, Rigging, and Systems Assemblers},
  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-51-2011-00}
}

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

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