Creative and Performing Artists Not Elsewhere Classified

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 4 task statements that define Creative and Performing Artists Not Elsewhere Classified (ISCO-08 2659) score an average of 0.13 on a 0–1 exposure scale — more exposed than about 10% 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 4 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Training and performing with animals.”

Scores 0.18 on the 2025 scale. The task of "Training and performing with animals" primarily involves high levels of physical interaction and complex, real-time decision-making based on animal behavior, which generative AI cannot currently replicate. Similar tasks in the context provided, such as "Preparing animals for training, conducting, and relocating" and "Developing a training plan for horses," also require nuanced understanding and hands-on care, resulting in scores around 0.18 to 0.20, indicating limited automation potential due to the need for human expertise and involvement. AI may assist with peripheral tasks such as record-keeping, scheduling, or providing general guidelines, but the core aspects of animal training and performance remain dependent on human skill and presence. In a high-income country like Poland, with good technological infrastructure, these supportive roles of AI might be optimally utilized, but the core physical and interactive tasks are still predominantly human-dominated, justifying a slightly lower automation potential in line with similar physically involved tasks.

Moving fastest, 2023 → 2025

“Training and performing with animals.”

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 2659, 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.

• Entertainers and Performers, Sports and Related Workers, All Other

In context

Part of the 2 - Professionals major group. Return to the full gradient to see how the whole group sits.

Creative and Performing Artists Not Elsewhere Classified sit at the 10th percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Creative and Performing Artists Not Elsewhere Classified rank in the 10th 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 0.07 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Training and performing with animals.". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Creative and Performing Artists Not Elsewhere Classified". https://singulariki.com/gradient/2659-creative-and-performing-artists-not-elsewhere-classified.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.