Teaching Professionals Not Elsewhere Classified

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 12 task statements that define Teaching Professionals Not Elsewhere Classified (ISCO-08 2359) score an average of 0.33 on a 0–1 exposure scale — more exposed than about 61% 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 Minimal 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 12 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Revising curricula, course content, course materials and methods of instruction”

Scores 0.53 on the 2025 scale. The task of revising curricula, course content, course materials, and methods of instruction involves a blend of content generation, strategic planning, and pedagogical oversight. Generative AI can assist in generating drafts of educational materials, suggesting improvements based on existing data, and organizing information for curricula development. However, similar tasks such as "Developing methodological materials and textbooks for teachers" and "Improving the scope, content of programs, and teaching methods" involve creativity, knowledge of pedagogical principles, and sensitivity to educational goals, which require human judgment and contextual understanding. These tasks received adjusted scores of 0.58 and 0.4, respectively, highlighting the supportive but limited role AI can play. Considering the high digital access in Poland, where AI tools are readily available, the automation score can reflect the potential for AI to streamline repetitive aspects of curriculum revision while acknowledging the need for human expertise to tailor content to specific educational needs and standards. Thus, the adjusted score of 0.5 represents a balance between AI's capabilities and the necessity for human oversight.

Moving fastest, 2023 → 2025

“Preparing students for later educational experiences by encouraging them to explore learning opportunities and to persevere with challenging tasks.”

Model capability on this task changed by +0.18 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 2359, 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.

• Educational, Guidance, and Career Counselors and Advisors
• Teachers and Instructors, All Other
• Educational Instruction and Library Workers, All Other

In context

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

Teaching Professionals Not Elsewhere Classified sit at the 61st percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Teaching Professionals Not Elsewhere Classified rank in the 61st 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 0.09 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Revising curricula, course content, course materials and methods of instruction". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Teaching Professionals Not Elsewhere Classified". https://singulariki.com/gradient/2359-teaching-professionals-not-elsewhere-classified.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.