Potters and Related Workers

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 11 task statements that define Potters and Related Workers (ISCO-08 7314) score an average of 0.18 on a 0–1 exposure scale — more exposed than about 26% 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 11 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Reading technical drawings to know customer‚Äôs requirements;”

Scores 0.34 on the 2025 scale. Reading technical drawings to understand customer requirements involves interpreting visual and technical information, which Generative AI can assist with to an extent. Similar tasks like "Reading technical and workshop drawings" and "Utilizing technical documentation" have adjusted scores around 0.30 to 0.35, highlighting moderate potential for automation particularly in the interpretation and parsing of digital data from technical drawings. However, this task also requires specific domain knowledge, human judgment, and the ability to understand complex design intricacies that are currently beyond AI capabilities. While AI can automate suggestions and provide clarifications, the necessity of human expertise for nuanced comprehension and decision-making remains essential. In the context of a highly connected setting like Poland, AI can significantly facilitate components of the task but cannot fully automate it. This justifies a moderate automation potential similar to related tasks that involve digital interpretation with supplemental human oversight.

Moving fastest, 2023 → 2025

“Preparing work for sale or exhibition, and maintaining relationships with retail, pottery, art and resource networks that can facilitate sale or exhibition of work.”

Model capability on this task changed by +0.16 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 7314, 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.

• Molders, Shapers, and Casters, Except Metal and Plastic
• Stone Cutters and Carvers, Manufacturing
• Glass Blowers, Molders, Benders, and Finishers
• Potters, Manufacturing
• Craft Artists

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.

Potters and Related Workers sit at the 26th percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Potters and Related Workers rank in the 26th 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: "Reading technical drawings to know customer‚Äôs requirements;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Potters and Related Workers". https://singulariki.com/gradient/7314-potters-and-related-workers.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.