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Structural Iron and Steel Workers

Occupation · SOC 47-2221.00

Raise, place, and unite iron or steel girders, columns, and other structural members to form completed structures or structural frameworks. May erect metal storage tanks and assemble prefabricated metal buildings.

Also called: Fitter · Iron Worker · Ironworker · Steel Worker · Steel Fabricator · Structural Steel Erector · Tower Hand · Assembler · Awnings Mechanic · Billboard Erector · Billboard Installer · Billboard Mechanic

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-47-2221-00/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.

2nd-percentile task overlap — yet about 5,500 openings a year (+4.4% 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 2nd -1.8
LLM task exposure, γ (OpenAI / Eloundou) Low 8th 0.1
AI assistant applicability (Microsoft) Low 5th 0.0

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.

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 0.8 · 68th 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 About average · +4.4% by 2034
Projected annual openings 5,500
Employment 2024 → 2034 65,700 → 68,600

“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)
5th percentile of 427 placed occupations
−1 pts shift 2023 → 2025
International occupation (ISCO-08) Task exposure (2025) Most tasks fall in
Structural Metal Preparers and Erectors · 7214 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 20 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.

Emerging tasks

Newer responsibilities O*NET has flagged as growing for this occupation.

  • Assemble or inspect hoisting equipment or rigging, such as cables, pulleys, or hooks, to move heavy equipment or materials.
  • Lift steel beams, girders, or columns using cranes or forklifts, or by signaling hoisting equipment operators to lift or position structural steel members.

Work activities

Knowledge, skills & abilities

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

Knowledge

Building and Construction 4.6
Mechanical 3.7
Mathematics 3.5
Public Safety and Security 3.3
Administration and Management 3.0

Abilities

Multilimb Coordination 4.1
Static Strength 4.1
Visualization 4.0
Arm-Hand Steadiness 4.0
Manual Dexterity 4.0
Near Vision 4.0
Control Precision 3.9
Trunk Strength 3.9
Problem Sensitivity 3.8
Selective Attention 3.8
Extent Flexibility 3.8
Gross Body Equilibrium 3.8
Depth Perception 3.8
Finger Dexterity 3.6
Dynamic Strength 3.6
Far Vision 3.6
Rate Control 3.5
Reaction Time 3.5
Stamina 3.5
Information Ordering 3.4
Auditory Attention 3.4
Oral Comprehension 3.3
Hearing Sensitivity 3.3
Oral Expression 3.1
Deductive Reasoning 3.1
Response Orientation 3.1
Gross Body Coordination 3.1
Speech Recognition 3.1
Speech Clarity 3.1

Transferable skills

Coordination 3.6
Operations Monitoring 3.6
Operation and Control 3.6

Essential skills

Active Listening 3.1
Critical Thinking 3.1
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 Outlook Electronic mail software Hot technology
Cost estimating software Project management software
Inventory tracking software Inventory management software
Project scheduling software 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.

Wear Common Protective or Safety Equipment such as Safety Shoes, Glasses, Gloves, Hearing Protection, Hard Hats, or Life Jackets 5.0
Exposed to Sounds, Noise Levels that are Distracting or Uncomfortable 4.8
Outdoors, Exposed to All Weather Conditions 4.8
Spend Time Using Your Hands to Handle, Control, or Feel Objects, Tools, or Controls 4.7
Exposed to High Places 4.7
Spend Time Standing 4.6
Exposed to Very Hot or Cold Temperatures 4.5
Physical Proximity 4.5
Wear Specialized Protective or Safety Equipment such as Breathing Apparatus, Safety Harness, Full Protection Suits, or Radiation Protection 4.5
Work With or Contribute to a Work Group or Team 4.4
Contact With Others 4.4
Exposed to Contaminants 4.3
Health and Safety of Other Workers 4.3
Face-to-Face Discussions with Individuals and Within Teams 4.3
Exposed to Hazardous Equipment 4.3
Time Pressure 4.2
Exposed to Minor Burns, Cuts, Bites, or Stings 4.2
Importance of Being Exact or Accurate 4.1
Exposed to Extremely Bright or Inadequate Lighting Conditions 4.1
Work Outcomes and Results of Other Workers 4.0
In an Open Vehicle or Operating Equipment 3.9
Exposed to Cramped Work Space, Awkward Positions 3.9
Spend Time Walking or Running 3.9
Frequency of Decision Making 3.8
Impact of Decisions on Co-workers or Company Results 3.8
Spend Time Bending or Twisting Your Body 3.7
Freedom to Make Decisions 3.7
Coordinate or Lead Others in Accomplishing Work Activities 3.6
Level of Competition 3.6
Spend Time Making Repetitive Motions 3.6
Consequence of Error 3.6
Determine Tasks, Priorities and Goals 3.5
Exposed to Hazardous Conditions 3.5
Telephone Conversations 3.4
Indoors, Not Environmentally Controlled 3.4
Spend Time Keeping or Regaining Balance 3.4
Spend Time Climbing Ladders, Scaffolds, or Poles 3.4
Conflict Situations 3.4
Outdoors, Under Cover 3.3
Deal With External Customers or the Public in General 3.0

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: 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 42.1%
Less than a High School Diploma 33.7%
Post-Secondary Certificate 19.2%
Post-Baccalaureate Certificate 5.0%

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 3.7
Investigative 2.8
Artistic 1.4

Interest areas

Physical/Manual Labor 6.7
Engineering 4.1
Transportation/Machine Operation 2.9
Construction/Woodwork 2.2
Mechanics/Electronics 2.0
Mathematics/Statistics 1.6

Work styles

Dependability 3.0
Cautiousness 2.2
Attention to Detail 2.1
Stress Tolerance 1.9
Perseverance 1.8
Achievement Orientation 1.3

Wages & employment

U.S. · annual wages (BLS OEWS)

$42k10th$49k25th$63kMedian$83k75th$108k90th
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.
66k202469k2034 (proj.)+4.4% · 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 $42,000
25th percentile $49,090
Median (50th) $62,700
75th percentile $82,780
90th percentile $107,520
People employed 64,720

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 54,840 $62,870
Manufacturing · Sector 6,950 $60,870
Other Building Equipment Contractors · National industry 2,030 $76,010
Administrative and Support and Waste Management and Remediation Services · Sector 860 $46,310
Power and Communication Line and Related Structures Construction · National industry 670 $51,720
Temporary Help Services · National industry 590 $38,090
Real Estate and Rental and Leasing · Sector 420 $58,210
Poured Concrete Foundation and Structure Contractors · National industry 410 $75,640
Plumbing, Heating, and Air-Conditioning Contractors · National industry 400 $60,640
Other Services (except Public Administration) · Sector 280 $67,570
Professional, Scientific, and Technical Services · Sector 270 $58,900
Wholesale Trade · Sector 240 $44,860

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
Other Building Equipment Contractors · National industry 31.49× 2,030
Construction · Sector 16.09× 54,840
Power and Communication Line and Related Structures Construction · National industry 6.82× 670
Poured Concrete Foundation and Structure Contractors · National industry 3.78× 410
Manufacturing · Sector 1.3× 6,950
Plumbing, Heating, and Air-Conditioning Contractors · National industry 0.75× 400
Mining, Quarrying, and Oil and Gas Extraction · Sector 0.58× 140
Temporary Help Services · National industry 0.53× 590

Part of the Construction career cluster.

Exposure quadrant: AI task-overlap percentile vs Median pay Structural Iron and Steel Workers sits at the 2nd percentile of AI task-overlap and the 51st 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 Structural Iron and Steel Workers Construction Laborers Drywall and Ceiling Tile Installers Boilermakers Structural Metal Fabricators and Fitters Millwrights 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 Structural Iron and Steel Workers — 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 5th percentile of 427 international occupations.

Write a report on thisheadline · factoids · citation

Structural Iron and Steel Workers show 2nd-percentile AI task overlap — and about 5,500 annual U.S. openings

  • Structural Iron and Steel Workers rank in the 2nd 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 5,500 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 (+4.4%) from 2024 to 2034.BLS Employment Projections 2024–34
  • Median annual pay is $62,700, across about 64,720 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Structural Iron and Steel Workers show 2nd-percentile AI task overlap — and about 5,500 annual U.S. openings

• Structural Iron and Steel Workers rank in the 2nd 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 5,500 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 (+4.4%) from 2024 to 2034. (BLS Employment Projections 2024–34)
• Median annual pay is $62,700, across about 64,720 U.S. workers. (BLS OEWS (May 2024))

Source: Singulariki — "Structural Iron and Steel Workers". https://singulariki.com/roles/role-47-2221-00
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. "Structural Iron and Steel Workers." 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-47-2221-00

APA

Singulariki. (2026). Structural Iron and Steel Workers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-47-2221-00

BibTeX
@misc{singulariki-role-47-2221-00,
  title  = {Structural Iron and Steel Workers},
  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-47-2221-00}
}

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

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