Metal Polishers, Wheel Grinders and Tool Sharpeners

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 7 task statements that define Metal Polishers, Wheel Grinders and Tool Sharpeners (ISCO-08 7224) 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 7 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Monitoring machine operations to determine whether adjustments are necessary, and stopping machines when problems occur;”

Scores 0.28 on the 2025 scale. The task of monitoring machine operations to determine whether adjustments are necessary and stopping machines when problems occur requires both real-time monitoring and decision-making capabilities. This is similar to tasks in the context like "Supervising and adjusting used devices during operation" (score: 0.285) and "Adjusting the operation of machines during work, monitoring indications of control and measurement instruments" (score: 0.3). These tasks involve a mix of data interpretation and potential physical intervention, requiring human supervision due to the need for real-time responsiveness, nuanced judgment, and hands-on manipulation. Generative AI can aid by detecting anomalies or providing alerts based on data analytics, but the physical and judgmental aspects require a human operator. Given the high technological infrastructure in Poland, there remains potential for AI-supported monitoring and data analytics, but the task's need for human presence and decision-making limits full automation. Hence, an adjusted score closer to semantically similar tasks like "Supervising dust removal devices" (score: 0.28) reflects the current capabilities of AI in contributing to but not fully automating this task.

Moving fastest, 2023 → 2025

“Sharpening cutting tools and instruments using grinding wheels or mechanically operated grinding machines;”

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 7224, 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.

• Grinding and Polishing Workers, Hand
• Tool Grinders, Filers, and Sharpeners

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.

Metal Polishers, Wheel Grinders and Tool Sharpeners sit at the 21st percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Metal Polishers, Wheel Grinders and Tool Sharpeners 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 rose by 0.00 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Monitoring machine operations to determine whether adjustments are necessary, and stopping machines when problems occur;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Metal Polishers, Wheel Grinders and Tool Sharpeners". https://singulariki.com/gradient/7224-metal-polishers-wheel-grinders-and-tool-sharpeners.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.