Will AI replace Carpenters?
Most of the work in Carpenters 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 47-2031
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 (~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 16 tasks, ratedBased on real task-level AI scores — click to collapse
- Maintain records, document actions, and present written progress reports.
- Study specifications in blueprints, sketches, or building plans to prepare project layout and determine dimensions and materials required.
- Inspect ceiling or floor tile, wall coverings, siding, glass, or woodwork to detect broken or damaged structures.
- Maintain job records and schedule work crew.
- Follow established safety rules and regulations and maintain a safe and clean environment.
- Measure and mark cutting lines on materials, using a ruler, pencil, chalk, and marking gauge.
- Assemble and fasten materials to make frameworks or props, using hand tools and wood screws, nails, dowel pins, or glue.
- Shape or cut materials to specified measurements, using hand tools, machines, or power saws.
- Verify trueness of structure, using plumb bob and level.
- Erect scaffolding or ladders for assembling structures above ground level.
- Install structures or fixtures, such as windows, frames, floorings, trim, or hardware, using carpenters' hand or power tools.
- Remove damaged or defective parts or sections of structures and repair or replace, using hand tools.
- Anchor and brace forms and other structures in place, using nails, bolts, anchor rods, steel cables, planks, wedges, and timbers.
- Bore boltholes in timber, masonry or concrete walls, using power drill.
- Install rough door and window frames, subflooring, fixtures, or temporary supports in structures undergoing construction or repair.
- Dig or direct digging of post holes and set poles to support 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.