Will AI replace Maintenance and Repair Workers, General?
Most of the work in Maintenance and Repair Workers, General still leans on things AI struggles with — research rates its theoretical AI reach at only ~14%, and real-world use lower still.
O*NET-SOC 49-9071
How your 21 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 (~14%). 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 (~14%), 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 21 tasks, ratedBased on real task-level AI scores — click to collapse
- Record type and cost of maintenance or repair work.
- Order parts, supplies, or equipment from catalogs or suppliers.
- Diagnose mechanical problems and determine how to correct them, checking blueprints, repair manuals, or parts catalogs, as necessary.
- Design new equipment to aid in the repair or maintenance of machines, mechanical equipment, or building structures.
- Estimate costs to repair machinery, equipment, or building structures.
- Plan and lay out repair work, using diagrams, drawings, blueprints, maintenance manuals, or schematic diagrams.
- Perform routine maintenance, such as inspecting drives, motors, or belts, checking fluid levels, replacing filters, or doing other preventive maintenance actions.
- Inspect, operate, or test machinery or equipment to diagnose machine malfunctions.
- Adjust functional parts of devices or control instruments, using hand tools, levels, plumb bobs, or straightedges.
- Repair machines, equipment, or structures, using tools such as hammers, hoists, saws, drills, wrenches, or equipment such as precision measuring instruments or electrical or electronic testing devices.
- Assemble, install, or repair wiring, electrical or electronic components, pipe systems, plumbing, machinery, or equipment.
- Clean or lubricate shafts, bearings, gears, or other parts of machinery.
- Align and balance new equipment after installation.
- Maintain or repair specialized equipment or machinery located in cafeterias, laundries, hospitals, stores, offices, or factories.
- Dismantle machines, equipment, or devices to access and remove defective parts, using hoists, cranes, hand tools, or power tools.
- Install equipment to improve the energy or operational efficiency of residential or commercial buildings.
- Set up and operate machine tools to repair or fabricate machine parts, jigs, fixtures, or tools.
- Perform general cleaning of buildings or properties.
- Train or manage maintenance personnel or subcontractors.
- Fabricate or repair counters, benches, partitions, or other wooden structures, such as sheds or outbuildings.
- Paint or repair roofs, windows, doors, floors, woodwork, plaster, drywall, or other parts of building structures.
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.