Veterinary Technicians and Assistants

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 10 task statements that define Veterinary Technicians and Assistants (ISCO-08 3240) score an average of 0.14 on a 0–1 exposure scale — more exposed than about 15% 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 10 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Producing radiographs, collecting samples and performing other laboratory tests to assist in diagnosis of animal health problems;”

Scores 0.18 on the 2025 scale. The task of producing radiographs, collecting samples, and performing laboratory tests to assist in diagnosing animal health problems involves a mix of technical and manual skills. Generative AI can assist in the analysis of radiographic images and data processing but lacks the physical capability to operate radiographic equipment or collect samples, which require human intervention. Similar tasks, such as "Conducting periodic health status checks of randomly selected laboratory animals," scored 0.18 and "Performing clinical analytics research for veterinary practitioners," scored 0.255, demonstrate partial AI assistance potential due to data processing capabilities. This task's need for hands-on skills aligns it more closely with the lower end of the adjusted scores. Considering the capabilities of AI for assisting but not fully automating the task in a context such as Poland, an adjusted score of 0.205 reflects the moderate potential for AI support without replacing human expertise in these medical and technical processes.

Moving fastest, 2023 → 2025

“Producing radiographs, collecting samples and performing other laboratory tests to assist in diagnosis of animal health problems;”

Model capability on this task changed by +0.08 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 3240, 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.

• Veterinary Technologists and Technicians
• Veterinary Assistants and Laboratory Animal Caretakers

In context

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

Veterinary Technicians and Assistants sit at the 15th percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Veterinary Technicians and Assistants rank in the 15th 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 0.02 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Producing radiographs, collecting samples and performing other laboratory tests to assist in diagnosis of animal health problems;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Veterinary Technicians and Assistants". https://singulariki.com/gradient/3240-veterinary-technicians-and-assistants.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.