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Glaziers

Construction, Maintenance & Repair
Projected change 2024–34: +3.3%
Median annual wage (2024): $55,440
Employment (2024): 61K

United States · BLS Employment Projections 2024–34 (figures for SOC 47-2121 occupational group)

AI exposure in published research

Figures below are reproduced from external datasets without modification. Where a dataset does not cover this occupation, the value is shown as — rather than as zero.

Data provider: OpenAI · "GPTs are GPTs"

Time basis: 2023 baselineex-ante estimate

Scored against GPT-4-generation capability.

Human rater basis
3.1%
GPT-4 rater basis
8.3%

β = direct exposure (E1) + 0.5 × exposure when tools are available (E2), per the source repository's definition.

27 rated tasks · 5 tasks with β ≥ 0.5 (18.5%)

Version:
gh-main-0471612
License:
MIT License · Copyright (c) 2024 OpenAI

Data provider: Anthropic Economic Index

Time basis: Published 2026-03-05composite index

Observed exposure
0.0%

Theoretical exposure index weighted by measured Claude usage, per the original report's definition.

27 tasks · usage observed in 0 · mean 0.0%

Data: Anthropic Economic Index — labor_market_impacts, CC-BY, https://huggingface.co/datasets/Anthropic/EconomicIndex

AI Changing Work uses Anthropic Economic Index data under CC-BY; Anthropic does not endorse or sponsor this site or its analyses.

Version:
hf-lmi-2026-03
License:
CC BY 4.0
Observation period:
(not applicable to this release)
Model:
(not stated by the source)

2023 prediction vs observation-based index published 2026-03-05

One card (GPTs are GPTs) is a 2023 estimate of what AI could theoretically do; the other (Anthropic Economic Index) is built from observed usage and was published on 2026-03-05 — that is its publication date, not the period it observed. They measure different things, so the two figures cannot be added, averaged, or ranked against each other. The older figure is kept here as a baseline for comparison rather than removed.

Caution: the Anthropic figures — observed exposure and task penetration — take the Eloundou β as one of their inputs. The two sides resembling each other is therefore not evidence that the earlier prediction came true; reading it that way is circular reasoning.

The Anthropic figures are measured on Claude users, who are not the whole economy and not the whole workforce.

The mapping of O*NET tasks and occupation codes was performed by AI Changing Work. The source figures themselves were not modified.

These indices are not forecasts. Which point in time each one belongs to is stated on the badge on its card.

Task Breakdown

  • Read blueprints and measure installation areas
  • Cut and shape glass to specifications
  • Install glass panels and secure with sealants
  • Estimate material costs and prepare quotes

About This Occupation

If you work as a Glazier, AI is reshaping your profession. With an automation risk of 4/100 and overall exposure at 6%, this role faces very-low transformation. The highest-impact area is estimate material costs and prepare quotes at 40% automation. This is classified as an 'augment' role. BLS projects 5% growth through 2034. Glass cutting and installation remain firmly hands-on trades, though AI-assisted measurement tools and cost estimation software are beginning to streamline the planning side of the work.

ISCO-08 classification

Unit group 7125ILO official

Glaziers

Definition

ILO original text (English)

Glaziers measure, cut, finish, fit and install flat glass and mirrors.

Definition & vocabulary source

Source: International Labour Organization (ILO) — ISCO-08 Structure

License: ILO CC BY 4.0

View original

Official occupational information

  • ONET47-2121.00

    Glaziers

    Install glass in windows, skylights, store fronts, and display cases, or on surfaces, such as building fronts, interior walls, ceilings, and tabletops.

    View original

Source: O*NET 30.2, U.S. DOL/ETA

License: CC BY 4.0

View original

Frequently Asked Questions

The Anthropic Economic Index puts observed exposure at 0.0%. The OpenAI "GPTs are GPTs" rubric puts occupation-level β at 3.1% under human raters. Both figures are reproduced from published research without modification.

They come from two published datasets: the Anthropic Economic Index (labor_market_impacts, CC BY 4.0) and the OpenAI "GPTs are GPTs" exposure rubric (MIT License, Copyright (c) 2024 OpenAI). AI Changing Work maps them onto O*NET occupation and task codes and does not calculate exposure scores of its own. AI Changing Work uses Anthropic Economic Index data under CC-BY; Anthropic does not endorse or sponsor this site or its analyses.

No. They are a diagnosis of exposure as measured at the time each source dataset was published. AI Changing Work publishes no prediction of future automation or job displacement for this occupation.

Recent Changes Affecting This Occupation

Mar 2026: Evergreen blog post published analyzing AI impact on glaziers (4% exposure, 3/100 risk).

[Source: AI Changing Work Blog]