Jewellery and Precious Metal Workers

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 11 task statements that define Jewellery and Precious Metal Workers (ISCO-08 7313) score an average of 0.18 on a 0–1 exposure scale — more exposed than about 25% 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

“Examining assembled or finished products to ensure conformance to specifications, using magnifying glasses or precision measuring instruments.”

Scores 0.28 on the 2025 scale. The task of examining assembled or finished products to ensure conformance to specifications requires a combination of precision inspection, potentially involving both visual and tactile assessment, which are capabilities that Generative AI currently lacks the ability to fully automate. This is similar to tasks like "Checking the correctness of sewing completion" (adjusted score 0.265) and "Detecting and removing defective work and leaks in precision devices and instruments" (adjusted score 0.285), both of which involve significant human sensory and judgment capability. Furthermore, the task connects closely to "Checking the quality of tools, molds, preforms, and mechanical devices for plastic forming" (adjusted score 0.17) and "Quality control of processes, semi-finished products, and finished goods" (adjusted score 0.195), where the need for hands-on inspection and nuanced decision-making reduces automation potential. Therefore, while AI can assist by providing data analysis or guiding the inspection process through highlighting discrepancies, the nuanced sensory judgment required for ensuring conformance to specifications limits full automation. Consequently, based on these comparatives and the high dependency on human oversight, an adjusted score of 0.32 reflects the realistic capabilities of Generative AI in this context.

Moving fastest, 2023 → 2025

“Examining assembled or finished products to ensure conformance to specifications, using magnifying glasses or precision measuring instruments.”

Model capability on this task changed by +0.18 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 7313, 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.

• Jewelers and Precious Stone and Metal Workers
• Gem and Diamond Workers

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.

Jewellery and Precious Metal Workers sit at the 25th percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Jewellery and Precious Metal Workers rank in the 25th 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 0.03 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Examining assembled or finished products to ensure conformance to specifications, using magnifying glasses or precision measuring instruments.". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Jewellery and Precious Metal Workers". https://singulariki.com/gradient/7313-jewellery-and-precious-metal-workers.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.