Garment and Related Patternmakers and Cutters

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 12 task statements that define Garment and Related Patternmakers and Cutters (ISCO-08 7532) score an average of 0.17 on a 0–1 exposure scale — more exposed than about 21% 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 12 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Creating the blueprint or pattern pieces for a particular apparel design with the aid of a computer;”

Scores 0.25 on the 2025 scale. The task of creating a blueprint or pattern pieces for apparel design with a computer involves a blend of creative design and technical skill, which Generative AI can assist by generating pattern suggestions and optimizing material usage. However, the task requires significant human expertise to evaluate material properties, interpret design intent, and execute precise adjustments, limiting the potential for full automation, much like the other tasks in the provided context. Semantically similar tasks, such as "Arranging templates on the surface of spread out clothing material and tracing their contours" (score 0.135) and "Selection of materials for new patterns" (score 0.164), have low scores due to their physical and manual components. Generative AI's capabilities can partially automate the ideation and basic generation phases of pattern-making but cannot fully replace the nuanced decision-making and hands-on skills required to create precise garment patterns. Considering these factors, and assuming the task takes place in a resource-rich environment like Poland, the adjusted score of 0.25 reflects the limited but existing potential for AI involvement in this creative and technical task.

Moving fastest, 2023 → 2025

“Testing patterns by making and fitting sample garments;”

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 7532, 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.

• Textile Cutting Machine Setters, Operators, and Tenders
• Cutters and Trimmers, Hand
• Fabric and Apparel Patternmakers

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.

Garment and Related Patternmakers and Cutters sit at the 21st percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Garment and Related Patternmakers and Cutters rank in the 21st 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 0.11 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Creating the blueprint or pattern pieces for a particular apparel design with the aid of a computer;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Garment and Related Patternmakers and Cutters". https://singulariki.com/gradient/7532-garment-and-related-patternmakers-and-cutters.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.