Production Clerks

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 5 task statements that define Production Clerks (ISCO-08 4322) score an average of 0.44 on a 0–1 exposure scale — more exposed than about 81% of the 427 placed occupations. Roughly 100% of its tasks fall somewhere on the exposed part of the gradient, and the typical task lands in the Gradient 2 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 5 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Preparing or assisting in the preparation of production operation schedules on the basis of customers' orders and production capacity and performance;”

Scores 0.54 on the 2025 scale. The task of preparing or assisting in the preparation of production operation schedules based on customer orders and production capacity is highly data-driven and involves routine administrative processes well-suited for automation through Generative AI. Comparing this task to semantically similar tasks within the higher-scoring range in the given context, notably those involving processing and analyzing information, such as "Calculating and paying contributions to the Social Security Institution" (adjusted score of 0.7) and "Analyzing algorithms and data processing programs" (adjusted score of 0.77), highlights AI's strong capabilities in handling structured, data-centric tasks. The task's resemblance to "Preparing purchase (sales) offers of goods for various recipients and clients" (adjusted score of 0.7) further supports its potential for automation, given the role's requirement for analyzing orders and capacity constraints and scheduling processes that AI can efficiently optimize. Given the structured nature of this task, its reliance on data management, and Poland's high technological infrastructure, an adjusted score of 0.62 reasonably reflects the potential for significant automation by Generative AI, while acknowledging the need for human oversight for strategic and nuanced decision-making.

Moving fastest, 2023 → 2025

“Recording and coordinating the flow of work and materials between departments.”

Model capability on this task changed by −0.01 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 4322, 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.

• Production, Planning, and Expediting Clerks

In context

Part of the 4 - Clerical support workers major group. Return to the full gradient to see how the whole group sits.

Production Clerks sit at the 81st percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Production Clerks rank in the 81st 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 100% of this occupation's tasks fall into an exposed gradient band. (ILO / Gmyrek et al. (2025))
• Mean task exposure fell by 0.16 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Preparing or assisting in the preparation of production operation schedules on the basis of customers' orders and production capacity and performance;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Production Clerks". https://singulariki.com/gradient/4322-production-clerks.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.