Cooks

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 7 task statements that define Cooks (ISCO-08 5120) score an average of 0.18 on a 0–1 exposure scale — more exposed than about 29% 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 7 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Planning, supervising and coordinating the work of kitchen helpers;”

Scores 0.29 on the 2025 scale. The task of planning, supervising, and coordinating the work of kitchen helpers involves several elements that are semantically similar to other supervision and management roles in the context, like "Supervising other employees in the field of design and construction execution" and "Supervising and coordinating the implementation of telecommunication services for individual clients," both of which emphasize human judgment, adaptability, and decision-making. Generative AI can aid in organizational aspects, such as scheduling and task management, but the dynamic human interactions and the need for immediate problem-solving inherent in kitchen supervision limit full automation potential. Similar supervisory roles within the provided cluster have shown moderate automation potential, with adjusted scores indicating limited capability for AI to fully automate such interpersonal and situative roles. Considering the balance of AI's supportive role in organizing and overseeing processes against the necessity for human supervision to ensure efficiency and address unforeseen issues, the adjusted score reflects AI's ability to assist in organizational tasks while emphasizing the ongoing critical need for human leadership and flexibility. Adjustments consider the high digital literacy in a high-income country like Poland where AI tools could support but not replace human functions in this context.

Moving fastest, 2023 → 2025

“Regulating the temperature of ovens, grills, roasters and other cooking equipment”

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 5120, 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.

• Cooks, Restaurant
• First-Line Supervisors of Food Preparation and Serving Workers
• Cooks, Institution and Cafeteria
• Cooks, Short Order
• Cooks, All Other
• Cooks, Private Household

In context

Part of the 5 - Service and sales workers major group. Return to the full gradient to see how the whole group sits.

Cooks sit at the 29th percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Cooks rank in the 29th 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: "Planning, supervising and coordinating the work of kitchen helpers;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Cooks". https://singulariki.com/gradient/5120-cooks.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.