Subsistence Mixed Crop and Livestock Farmers

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 9 task statements that define Subsistence Mixed Crop and Livestock Farmers (ISCO-08 6330) score an average of 0.12 on a 0–1 exposure scale — more exposed than about 6% 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 9 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Selling or bartering some products at local markets.”

Scores 0.21 on the 2025 scale. The task of selling or bartering products at local markets involves direct human interaction, negotiation skills, and physical presence, which are not fully automatable by Generative AI. While AI can assist with aspects like inventory management, pricing strategies, and digital marketing efforts, the core activities of engaging customers, understanding their needs, and closing sales remain human-centric. This task is similar to "Replenishing the assortment of goods for sale" (automation score: 0.175), which also involves decision-making based on physical product management and customer engagement, both requiring human involvement. Additionally, tasks such as "Promoting new culinary products and beverages" and "Serving customers purchasing goods in small-scale direct retail sales" have scores reflecting the need for human interaction despite AI's support potential. Considering these parallels and the limitations of AI in replacing human negotiation and physical activities, an adjusted score of 0.1775 is justified. This reflects the limited but existing potential for AI to aid peripheral tasks in a high-income country like Poland, where technology access could enhance the support role of AI without enabling full automation.

Moving fastest, 2023 → 2025

“Breeding, tending and feeding animals and poultry mainly to obtain meat, eggs, milk, hair, skin or other products;”

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 6330, 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.

• Farmworkers and Laborers, Crop, Nursery, and Greenhouse
• Farmworkers, Farm, Ranch, and Aquacultural Animals

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.

Subsistence Mixed Crop and Livestock Farmers sit at the 6th percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Subsistence Mixed Crop and Livestock Farmers rank in the 6th 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: "Selling or bartering some products at local markets.". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Subsistence Mixed Crop and Livestock Farmers". https://singulariki.com/gradient/6330-subsistence-mixed-crop-and-livestock-farmers.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.