Livestock and Dairy Producers

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 13 task statements that define Livestock and Dairy Producers (ISCO-08 6121) score an average of 0.17 on a 0–1 exposure scale — more exposed than about 22% 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 13 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Monitoring market activity and conditions, determining kinds and amounts of stock to produce, planning and coordinating production accordingly;”

Scores 0.43 on the 2025 scale. The task of monitoring market activity, determining stock production kinds and amounts, and coordinating production involves a combination of data analysis, decision-making, and strategic planning. Generative AI can significantly aid in market analysis, trend identification, and basic decision-support by providing data-driven insights, much like the tasks related to managing inventory (0.365) and analyzing production processes (0.3525), which also involve strategic data interpretation and decision-making. However, these tasks still require human expertise for nuanced decision-making and adapting to real-world complexities. Similar tasks like "Organizing the storage of products and preparing them for sale" and "Replenishing the assortment of goods for sale," scored at around 0.135 and 0.175 respectively, underline the manual and strategic components, though they are more physically inclined compared to production planning. Considering Poland's technological infrastructure, which enables effective AI application, yet recognizing the essential role of human insight in planning and strategic decisions, this task exhibits moderate automation potential. Therefore, an adjusted score of 0.41 reflects the blend of AI's capability in data analysis with the necessity for human oversight in strategic elements of production planning and response to market dynamics.

Moving fastest, 2023 → 2025

“Training and supervising workers in animal care procedures, maintenance duties, and health and safety precautions, and hiring and discharging workers and contractors.”

Model capability on this task changed by +0.11 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 6121, 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.

• First-Line Supervisors of Farming, Fishing, and Forestry Workers
• Animal Breeders

In context

Part of the 6 - Skilled agricultural, forestry and fishery workers major group. Return to the full gradient to see how the whole group sits.

Livestock and Dairy Producers sit at the 22nd percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Livestock and Dairy Producers rank in the 22nd 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 0.01 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Monitoring market activity and conditions, determining kinds and amounts of stock to produce, planning and coordinating production accordingly;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Livestock and Dairy Producers". https://singulariki.com/gradient/6121-livestock-and-dairy-producers.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.