Will AI replace Structural Iron and Steel Workers?
Most of the work in Structural Iron and Steel Workers still leans on things AI struggles with — research rates its theoretical AI reach at only ~3%, and real-world use lower still.
O*NET-SOC 47-2221
How your 15 core tasks split
Top = what GPT-4 judged AI could speed up. Bottom = how much AI was actually used for these tasks (Anthropic's March 2026 report, usage from Aug & Nov 2025). The gap is the real story.
Back in 2023, GPT-4 judged AI could, in theory, assist with a relatively low share of this job's tasks (~3%). By late 2025, real-world AI use had caught up to about 5% of its task activity (still rare). The gap between that 2023 forecast and today is the real story.
Where this job sits among 738 jobs
Each dot is one of 738 U.S. jobs. Right = AI can do more of it. Up = AI is actually used more.
The signals here line up
Theoretical reach (~3%), real-world use (~5%) and the task-level picture mostly agree — so this read is more reliable than for jobs where the signals contradict each other. Even so, AI-risk estimates shift by model (a 2026 study saw the "high-risk" share swing 2.7%–51.5%), so treat these as directional, not destiny.
See all 15 tasks, ratedBased on real task-level AI scores — click to collapse
- None — AI cannot fully do any core task alone yet.
- Read specifications or blueprints to determine the locations, quantities, or sizes of materials required.
- Connect columns, beams, and girders with bolts, following blueprints and instructions from supervisors.
- Bolt aligned structural steel members in position for permanent riveting, bolting, or welding into place.
- Fasten structural steel members to hoist cables, using chains, cables, or rope.
- Hoist steel beams, girders, or columns into place, using cranes or signaling hoisting equipment operators to lift and position structural steel members.
- Verify vertical and horizontal alignment of structural steel members, using plumb bobs, laser equipment, transits, or levels.
- Cut, bend, or weld steel pieces, using metal shears, torches, or welding equipment.
- Erect metal or precast concrete components for structures, such as buildings, bridges, dams, towers, storage tanks, fences, or highway guard rails.
- Force structural steel members into final positions, using turnbuckles, crowbars, jacks, or hand tools.
- Pull, push, or pry structural steel members into approximate positions for bolting into place.
- Unload and position prefabricated steel units for hoisting, as needed.
- Drive drift pins through rivet holes to align rivet holes in structural steel members with corresponding holes in previously placed members.
- Assemble hoisting equipment or rigging, such as cables, pulleys, or hooks, to move heavy equipment or materials.
- Fabricate metal parts, such as steel frames, columns, beams, or girders, according to blueprints or instructions from supervisors.
- Dismantle structures or equipment.
How we measured this — and how fresh it is
AI's theoretical reach data: 2023
From GPTs-are-GPTs (Eloundou et al.), where GPT-4 rated how much of each task an AI tool could meaningfully speed up. This is the most recent open, commercially-usable occupation-level potential dataset — it dates to 2023. Newer multi-model re-runs exist but swing wildly (one 2026 study saw "high-risk" jobs range 2.7%–51.5% by model) and aren't openly licensed, so we show the stable 2023 baseline and pair it with newer real-world data.
Real-world AI use 2026 report
From the Anthropic Economic Index, which observes how real Claude conversations map onto each occupation's tasks. Published in Anthropic's March 2026 labor-market report, based on usage measured in Aug & Nov 2025 (Sonnet 4 / 4.5).
Task list & ratings O*NET 30.3
Tasks come from O*NET 30.3. Each task's "AI can do / speeds up / still on you" tier uses the real task-level exposure scores from GPTs-are-GPTs (E1 / E2 / E0) — not a guess from keywords.
Sources: O*NET 30.3 (CC BY 4.0) · GPTs-are-GPTs (MIT, 2023) · Anthropic Economic Index (CC BY, Aug & Nov 2025). Page compiled June 2026. "O*NET" is a trademark of the U.S. Department of Labor.
This page is for general informational purposes only and is not career, financial, or employment advice. AI exposure reflects research estimates of task overlap, not predictions about any individual's job, employer, or future employment.