Glaziers

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 4 task statements that define Glaziers (ISCO-08 7125) score an average of 0.14 on a 0–1 exposure scale — more exposed than about 13% of the 427 placed occupations. Roughly 0% of its tasks fall somewhere on the exposed part of the gradient, and the typical task lands in the Not exposed band.

Exposure is task overlap, not a verdict. A high score means a generative-AI model can do part of the content of these tasks — it says nothing about whether the work is automated, whether anyone uses AI for it today, or whether jobs are lost. The gradient is scored on the international ISCO-08 system; the rest of Singulariki is U.S. O*NET/SOC, bridged below by an approximate, many-to-many crosswalk.

How its tasks split across the gradient

Each of the 4 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Creating decorative glass features such as glass walls, staircases, balustrades and stained-glass windows.”

Scores 0.14 on the 2025 scale. The task of creating decorative glass features such as glass walls, staircases, balustrades, and stained-glass windows involves significant manual craftsmanship, artistic judgment, and precise physical manipulation. These skills require dexterity and visual assessment, which generative AI cannot fully automate. The semantically similar tasks, such as grinding glass edges, marking glass products by stamping, or gluing elements for embossing, also involve physical and tactile skills and have been assigned adjusted scores reflecting low automation potential due to the inherent hands-on nature of the work. For instance, glass processing tasks like grinding and polishing received adjusted scores around 0.13 to 0.15, indicating limited scope for automation. Given the high-income context of Poland, where there is good access to digital tools, AI might assist in the design phase but cannot replace the physical execution required to create unique and customized glass artworks. Therefore, the adjusted score reflects the partial assistance AI can offer in design but recognizes the task's reliance on skilled craftsmanship for its core execution.

Moving fastest, 2023 → 2025

“Creating decorative glass features such as glass walls, staircases, balustrades and stained-glass windows.”

Model capability on this task changed by +0.04 in two years — the gradient is not static, it is filling in.

U.S. occupations this maps to

The American O*NET/SOC roles that crosswalk to ISCO-08 7125, biggest by employment first, via the published (approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 correspondence. These are the closest U.S. matches — not an asserted one-to-one identity.

• Glaziers

In context

Part of the 7 - Craft and related trades workers major group. Return to the full gradient to see how the whole group sits.

Glaziers sit at the 13th percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Glaziers rank in the 13th percentile for GenAI task exposure — overlap with what generative AI can attempt, not a projection of displacement. (ILO / Gmyrek et al. (2025) GenAI exposure gradient)
• About 0% of this occupation's tasks fall into an exposed gradient band. (ILO / Gmyrek et al. (2025))
• Mean task exposure rose by 0.04 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Creating decorative glass features such as glass walls, staircases, balustrades and stained-glass windows.". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Glaziers". https://singulariki.com/gradient/7125-glaziers.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.