Chemical Engineering Technicians

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 5 task statements that define Chemical Engineering Technicians (ISCO-08 3116) 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 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 5 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Conducting chemical and physical laboratory tests to assist scientists and engineers in making qualitative and quantitative analyses of solids, liquids, and gaseous materials.”

Scores 0.35 on the 2025 scale. The task of conducting chemical and physical laboratory tests to assist scientists and engineers in analyzing materials shares similarities with the tasks of conducting measurements and testing electronic systems and chromalin material, which have adjusted scores of 0.35 and 0.19375 respectively. These tasks, like the current one, involve a combination of hands-on interaction with instruments and the need for contextual analysis and interpretation. Generative AI can assist in the analysis of data, documentation, and pattern recognition but lacks the capability to perform physical tasks and the nuanced judgment required for interpreting complex scientific data. The task also has elements similar to controlling the quality of products and performing load tests, which emphasize the need for human oversight and expertise. Considering the high accessibility to technology in a country like Poland, which allows for AI to facilitate data management, but not replace the intricacies of hands-on laboratory testing, the adjusted score reflects this balance of reliance on human expertise and AI assistance. The score accounts for the supportive role AI can play in automating parts of the testing process, while still acknowledging the essential human intervention in the physical and judgment-based components of the task.

Moving fastest, 2023 → 2025

“Conducting chemical and physical laboratory tests to assist scientists and engineers in making qualitative and quantitative analyses of solids, liquids, and gaseous materials.”

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 3116, 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.

• Engineering Technologists and Technicians, Except Drafters, All Other
• Non-Destructive Testing Specialists
• Photonics Technicians

In context

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

Chemical Engineering Technicians sit at the 60th percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Chemical Engineering Technicians 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 0.05 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Conducting chemical and physical laboratory tests to assist scientists and engineers in making qualitative and quantitative analyses of solids, liquids, and gaseous materials.". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Chemical Engineering Technicians". https://singulariki.com/gradient/3116-chemical-engineering-technicians.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.