Will AI replace Boilermakers?
Most of the work in Boilermakers 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 47-2011
How your 16 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 reached about 0% 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 (~0%) 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 16 tasks, ratedBased on real task-level AI scores — click to collapse
- None — AI cannot fully do any core task alone yet.
- Study blueprints to determine locations, relationships, or dimensions of parts.
- Attach rigging and signal crane or hoist operators to lift heavy frame and plate sections or other parts into place.
- Repair or replace defective pressure vessel parts, such as safety valves or regulators, using torches, jacks, caulking hammers, power saws, threading dies, welding equipment, or metalworking machinery.
- Locate and mark reference points for columns or plates on boiler foundations, following blueprints and using straightedges, squares, transits, or measuring instruments.
- Bolt or arc weld pressure vessel structures and parts together, using wrenches or welding equipment.
- Position, align, and secure structural parts or related assemblies to boiler frames, tanks, or vats of pressure vessels, following blueprints.
- Install manholes, handholes, taps, tubes, valves, gauges, or feedwater connections in drums of water tube boilers, using hand tools.
- Shape or fabricate parts, such as stacks, uptakes, or chutes, to adapt pressure vessels, heat exchangers, or piping to premises, using heavy-metalworking machines such as brakes, rolls, or drill presses.
- Assemble large vessels in an on-site fabrication shop prior to installation to ensure proper fit.
- Lay out plate, sheet steel, or other heavy metal and locate and mark bending and cutting lines, using protractors, compasses, and drawing instruments or templates.
- Examine boilers, pressure vessels, tanks, or vats to locate defects, such as leaks, weak spots, or defective sections, so that they can be repaired.
- Shape seams, joints, or irregular edges of pressure vessel sections or structural parts to attain specified fit of parts, using cutting torches, hammers, files, or metalworking machines.
- Inspect assembled vessels or individual components, such as tubes, fittings, valves, controls, or auxiliary mechanisms, to locate any defects.
- Straighten or reshape bent pressure vessel plates or structure parts, using hammers, jacks, or torches.
- Install refractory bricks or other heat-resistant materials in fireboxes of pressure vessels.
- Clean pressure vessel equipment, using scrapers, wire brushes, and cleaning solvents.
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.