GistGarden

Will AI replace Helpers--Roofers?

Most of the work in Helpers--Roofers still leans on things AI struggles with — research rates its theoretical AI reach at only ~0%, and real-world use lower still.

The Human Moat Work that's hard for AI to cross — for now.

O*NET-SOC 47-3016

How your 18 core tasks split

0% within AI's reach
0 AI can do this now
0 AI speeds this up
18 Still on you
AI could do · GPT-4 study
0%
0-pt gap
AI actually does · 2026 report
0%

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.

⚡ The short answer

Back in 2023, GPT-4 judged AI could, in theory, assist with a relatively low share of this job's tasks (~0%). By late 2025, real-world AI use had caught up to 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

Being automatedTicking (can, but unused)Relatively safeQuietly happeningYOU0%50%100%0%40%75% → How much AI could do (theory) → How much AI is actually used (late 2025)

Each dot is one of 738 U.S. jobs. Right = AI can do more of it. Up = AI is actually used more.

Stableconfidence

The signals here line up

Theoretical reach (~0%), 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 18 tasks, ratedBased on real task-level AI scores — click to collapse
AI can already do this0 of 18
  • None — AI cannot fully do any core task alone yet.
AI speeds this up0 of 18
  • No tasks in this middle tier.
Still on you18 of 18
  • Check to ensure that completed roofs are watertight.
  • Sweep and clean roofs to prepare them for the application of new roofing materials.
  • Locate worn or torn areas in roofs.
  • Clean work areas and equipment.
  • Maintain tools and equipment.
  • Cover roofs with layers of roofing felt or asphalt strips before installing tile, slate, or composition materials.
  • Remove old roofing materials.
  • Unload materials and tools from work trucks, and unroll roofing as directed.
  • Set ladders, scaffolds, and hoists in place for taking supplies to roofs.
  • Place tiles, nail them to roof boards, and cover nailheads with roofing cement.
  • Provide assistance to skilled roofers installing and repairing roofs, flashings, and surfaces.
  • Attach roofing paper and composition shingles, using nails.
  • Perform emergency leak repairs and general maintenance for a variety of roof types.
  • Attach sheets of metal to roof boards or building frameworks when installing metal roofs.
  • Hoist tar and roofing materials to roofs, using ropes and pulleys, or carry materials up ladders.
  • Apply shingles, gravel, or asphalt over the top layer of tar to protect the roofing material.
  • Chop tar into small pieces, and heat chopped tar in kettles.
  • Clear drains and downspouts and clean gutters.

My job is a Human Moat 😌

Turns out being human is still the hard part to copy.

Theoretical estimate · not a prediction · gistgarden.com

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.