Concrete Placers, Concrete Finishers and Related Workers

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 5 task statements that define Concrete Placers, Concrete Finishers and Related Workers (ISCO-08 7114) score an average of 0.10 on a 0–1 exposure scale — more exposed than about 3% 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 5 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Making shuttering or assembling prefabricated forms for moulding concrete;”

Scores 0.14 on the 2025 scale. The task of making shuttering or assembling prefabricated forms for molding concrete is a highly manual and physical task involving precise manipulation and construction skills. Similar to other tasks in the cluster related to formwork, molds, and assemblage, it requires hands-on work that Generative AI currently cannot automate. For instance, tasks such as "Preparing individual parts of the mold, assembling, binding or stapling, and testing their tightness" received scores ranging from 0.13 to 0.15, reflecting their highly manual nature that limits AI automation potential. While AI can assist with planning or instructions, the physical act of assembly and manual craftsmanship required for shuttering remains firmly in the domain of human workers. The adjusted score accounts for the minimal role AI can play in direct task execution but recognizes potential support in planning or design optimization. Given the context of a high-income country with good access to AI assistance tools, this adjusted score of 0.13 reflects the task's alignment with those requiring significant human dexterity and intervention.

Moving fastest, 2023 → 2025

“Making shuttering or assembling prefabricated forms for moulding concrete;”

Model capability on this task changed by +0.09 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 7114, 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.

• Cement Masons and Concrete Finishers
• Terrazzo Workers and Finishers
• Segmental Pavers

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.

Concrete Placers, Concrete Finishers and Related Workers sit at the 3rd percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Concrete Placers, Concrete Finishers and Related Workers rank in the 3rd 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 0.01 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Making shuttering or assembling prefabricated forms for moulding concrete;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Concrete Placers, Concrete Finishers and Related Workers". https://singulariki.com/gradient/7114-concrete-placers-concrete-finishers-and-related-workers.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.