Assemblers Not Elsewhere Classified

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 5 task statements that define Assemblers Not Elsewhere Classified (ISCO-08 8219) score an average of 0.32 on a 0–1 exposure scale — more exposed than about 60% 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 5 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Recording production and operational data on specified forms;”

Scores 0.59 on the 2025 scale. Recording production and operational data on specified forms relates closely to tasks involving structured documentation, data entry, and record-keeping, such as maintaining process documentation or filling work reports, which have automation scores around 0.315 to 0.5025. This task benefits from Generative AI's strength in handling repetitive documentation and data processing tasks, enhancing efficiency in organizing and entering data. However, like other tasks that require human oversight for accuracy and context comprehension, recording data needs occasional human interventions for quality control, decision-making, and handling exceptions. Given the capability of AI in automating repetitive documentation tasks and the high digital literacy in Poland, an adjusted score of 0.53 reflects the balanced potential for automation with necessary human oversight.

Moving fastest, 2023 → 2025

“Assembling component parts and positioning, aligning and fastening units to assemblies, subassemblies or frames using hand or power tools, soldering and micro-welding equipment;”

Model capability on this task changed by +0.04 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 8219, 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.

• Team Assemblers
• Assemblers and Fabricators, All Other

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.

Assemblers Not Elsewhere Classified sit at the 60th percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Assemblers Not Elsewhere Classified rank in the 60th 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 0.03 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Recording production and operational data on specified forms;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Assemblers Not Elsewhere Classified". https://singulariki.com/gradient/8219-assemblers-not-elsewhere-classified.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.