Paper Products Machine Operators

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 3 task statements that define Paper Products Machine Operators (ISCO-08 8143) score an average of 0.18 on a 0–1 exposure scale — more exposed than about 27% 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 3 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Operating and monitoring machines which cut, fold and glue paper to make envelopes and paper bags, or which form bags from other similar material.”

Scores 0.20 on the 2025 scale. The task of operating and monitoring machines that cut, fold, and glue paper to make envelopes and paper bags involves significant manual interaction with machinery, which requires human dexterity and real-time decision-making. Similar semantically related tasks in the context, such as operating basic machines for clothing production (adjusted score 0.25) and operating grinders and saws for ceramics (adjusted score 0.16), emphasize the necessity for human involvement due to the physical nature of the work. While Generative AI can assist with monitoring through data analysis or offer guidance for operating procedures, it lacks the capability to perform the intricate physical tasks independently. Given the task's reliance on human oversight for troubleshooting and adjustments, and considering the capabilities of AI to aid but not fully automate these operations, an adjusted score of 0.22 reflects this limited scope for automation. This score considers the manual aspects and parallels drawn from similar tasks, while factoring in AI's role in optimizing certain non-physical elements like process monitoring and efficiency improvements.

Moving fastest, 2023 → 2025

“Operating and monitoring machines which cut, fold and glue paper to make envelopes and paper bags, or which form bags from other similar material.”

Model capability on this task changed by +0.10 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 8143, 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.

• Paper Goods Machine Setters, Operators, and Tenders
• Adhesive Bonding Machine Operators and Tenders

In context

Part of the 8 - Plant and machine operators, and assemblers major group. Return to the full gradient to see how the whole group sits.

Paper Products Machine Operators sit at the 27th percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Paper Products Machine Operators rank in the 27th 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: "Operating and monitoring machines which cut, fold and glue paper to make envelopes and paper bags, or which form bags from other similar material.". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Paper Products Machine Operators". https://singulariki.com/gradient/8143-paper-products-machine-operators.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.