Bakers, Pastry-cooks and Confectionery Makers

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 8 task statements that define Bakers, Pastry-cooks and Confectionery Makers (ISCO-08 7512) 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 8 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Checking the quality of raw materials to ensure that standards and specifications are met;”

Scores 0.35 on the 2025 scale. The task of checking the quality of raw materials to ensure that standards and specifications are met involves both objective measures like data analysis and subjective judgments involving sensory evaluation. Similar tasks, such as evaluating the quality of raw materials and semi-finished products (0.3525), assessing the quality of fresh produce (0.35), and evaluating material quality for industrial production (0.365), indicate a partial automation potential. Generative AI can assist by analyzing data patterns, providing insights on deviations from quality standards, and suggesting process optimizations. However, the need for human expertise in sensory evaluations, on-the-ground assessments, and nuance in decision-making limits full automation potential. This task, performed in a high-income country like Poland with good access to technology, allows AI to support but not fully replace human judgment. Consequently, the score of 0.355 reflects AI's supportive capacity while emphasizing the continued necessity for human oversight.

Moving fastest, 2023 → 2025

“Checking the cleanliness of equipment and operation of premises before production runs to ensure compliance with occupational health and safety regulations;”

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 7512, 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.

• Bakers

In context

Part of the 7 - Craft and related trades workers major group. Return to the full gradient to see how the whole group sits.

Bakers, Pastry-cooks and Confectionery Makers sit at the 22nd percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Bakers, Pastry-cooks and Confectionery Makers 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 rose by 0.03 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Checking the quality of raw materials to ensure that standards and specifications are met;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Bakers, Pastry-cooks and Confectionery Makers". https://singulariki.com/gradient/7512-bakers-pastry-cooks-and-confectionery-makers.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.