Product and Garment Designers

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 9 task statements that define Product and Garment Designers (ISCO-08 2163) score an average of 0.35 on a 0–1 exposure scale — more exposed than about 64% 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 Minimal 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 9 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Detailing and documenting the selected design for production;”

Scores 0.51 on the 2025 scale. The task of "Detailing and documenting the selected design for production" involves structured documentation and potentially standardized processes, highly active areas for Generative AI. This aligns closely with tasks like "Maintaining technological process documentation" or "Maintaining production process documentation," which received adjusted scores of 0.445 and 0.455, respectively. These similar tasks involve creating records or documents based on technical processes or designs, where Generative AI can assist by automating standard entries, managing templates, and ensuring consistency. However, like those tasks, the need for human expertise to interpret designs, ensure conformity to specific requirements, and adapt to unforeseen issues is critical, limiting full automation. Given the structured nature and the current capabilities of Generative AI, the potential for partial automation is moderate, considering the need for human oversight to ensure accurate implementation and compliance of documentation, especially in a technology-equipped environment like Poland. Thus, the task's adjusted score reasonably reflects AI's supportive role in documentation and needing expert input.

Moving fastest, 2023 → 2025

“Negotiating design solutions with clients, management, and sales and manufacturing staff;”

Model capability on this task changed by +0.15 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 2163, 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.

• Commercial and Industrial Designers
• Fashion Designers
• Designers, All Other

In context

Part of the 2 - Professionals major group. Return to the full gradient to see how the whole group sits.

Product and Garment Designers sit at the 64th percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Product and Garment Designers rank in the 64th 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 0.03 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Detailing and documenting the selected design for production;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Product and Garment Designers". https://singulariki.com/gradient/2163-product-and-garment-designers.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.