Cabinet-makers and Related Workers

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 6 task statements that define Cabinet-makers and Related Workers (ISCO-08 7522) score an average of 0.16 on a 0–1 exposure scale — more exposed than about 19% 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 6 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Studying plans, verifying dimensions of articles to be made, or preparing specifications and checking the quality and fit of pieces in order to ensure adherence to specifications;”

Scores 0.29 on the 2025 scale. The task of studying plans, verifying dimensions, preparing specifications, and checking the quality of pieces in adherence to specifications requires substantial human involvement and expertise in physical inspection and measurement. Tasks of evaluating and inspecting materials, like "Evaluating materials and semi-finished products for the production of inserts and orthopedic footwear" (adjusted score of 0.325), involve similar evaluation and quality assessment aspects. While Generative AI excels at processing and analyzing data, it lacks the capability for manual and sensory-based inspection required in this task. The predominant reliance on tactile feedback and human judgment limits the automation potential, aligning this task with others in the moderate automation potential range. Given the presence of advanced technology and infrastructure in a high-income country like Poland, AI could assist with documentation and data management but not replace the human component in detailed physical assessments, justifying the adjusted score of 0.325.

Moving fastest, 2023 → 2025

“Making, restyling and repairing various wooden articles, such as cabinets, furniture, vehicles, scale models, sports equipment and other parts or products;”

Model capability on this task changed by +0.05 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 7522, 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.

• Cabinetmakers and Bench Carpenters
• Furniture Finishers
• Model Makers, Wood
• Patternmakers, Wood

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.

Cabinet-makers and Related Workers sit at the 19th percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Cabinet-makers and Related Workers rank in the 19th 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 0.02 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Studying plans, verifying dimensions of articles to be made, or preparing specifications and checking the quality and fit of pieces in order to ensure adherence to specifications;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Cabinet-makers and Related Workers". https://singulariki.com/gradient/7522-cabinet-makers-and-related-workers.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.