Plasterers

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 7 task statements that define Plasterers (ISCO-08 7123) score an average of 0.11 on a 0–1 exposure scale — more exposed than about 5% 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 7 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Measuring, marking and installing ornamental plaster panels, and casting and trimming ornamental plaster cornices;”

Scores 0.14 on the 2025 scale. The task of measuring, marking, and installing ornamental plaster panels, and casting and trimming ornamental plaster cornices involves substantial manual labor, precise physical manipulation, and a high degree of craftsmanship. This aligns closely with tasks like "Creating models, molds, and casts of stucco work" (adjusted score: 0.1375) and "Performing trial casts on made molds" (adjusted score: 0.126), which are similarly dependent on manual dexterity and hands-on skills. Generative AI can support planning and provide instructional guidance, but it cannot replicate the physical execution required. The adjusted score accounts for these limitations, reflecting minimal automation potential, particularly in a well-equipped, high-income context like Poland, where technological infrastructure supports but does not replace such manual tasks.

Moving fastest, 2023 → 2025

“Making and installing decorative plaster fixtures of fibrous plaster;”

Model capability on this task changed by +0.07 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 7123, 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.

• Drywall and Ceiling Tile Installers
• Plasterers and Stucco Masons
• Tapers

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.

Plasterers sit at the 5th percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Plasterers rank in the 5th 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 fell by 0.01 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Measuring, marking and installing ornamental plaster panels, and casting and trimming ornamental plaster cornices;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Plasterers". https://singulariki.com/gradient/7123-plasterers.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.