Manufacturing Supervisors

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 6 task statements that define Manufacturing Supervisors (ISCO-08 3122) score an average of 0.35 on a 0–1 exposure scale — more exposed than about 63% 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 6 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Preparing cost estimates, records and reports;”

Scores 0.59 on the 2025 scale. The task of preparing cost estimates, records, and reports involves structured data processing, analysis, and documentation, areas where Generative AI excels. Similar tasks, such as calculating production and distribution costs (adjusted score: 0.615) and preparing reports (adjusted score: 0.65), show significant potential for automation due to their data-intensive nature. However, unlike purely numerical tasks or straightforward data entry, this task requires contextual understanding of cost factors, dynamic decision-making, and compliance with industry standards, which necessitate human oversight. In Poland, where digital infrastructure is advanced, AI can effectively assist in automating repetitive elements and preliminary calculations, streamlining the process. Thus, the adjusted score of 0.58 reflects the balance between AI's capability to handle structured tasks and the requisite human expertise for nuanced decision-making and validation in cost estimation and reporting.

Moving fastest, 2023 → 2025

“Ensuring safety of workers;”

Model capability on this task changed by +0.14 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 3122, 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.

• First-Line Supervisors of Production and Operating Workers

In context

Part of the 3 - Technicians and associate professionals major group. Return to the full gradient to see how the whole group sits.

Manufacturing Supervisors sit at the 63rd percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Manufacturing Supervisors rank in the 63rd 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 0.00 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Preparing cost estimates, records and reports;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Manufacturing Supervisors". https://singulariki.com/gradient/3122-manufacturing-supervisors.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.