Physiotherapists

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 7 task statements that define Physiotherapists (ISCO-08 2264) score an average of 0.28 on a 0–1 exposure scale — more exposed than about 53% 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 7 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Recording information on patients' health status and responses to treatment in medical records-keeping systems, and sharing information with other health professionals as required to ensure continuing and comprehensive care;”

Scores 0.56 on the 2025 scale. The task of recording information on patients' health status and responses to treatment in medical records-keeping systems involves structured data entry, organization, and management, similar to the task "Maintaining and storing patient health records in various classification systems," which had an adjusted score of 0.575. Generative AI can effectively automate repetitive aspects of this task, such as data entry and preliminary organization, by using natural language processing to transcribe interactions and format data into existing systems. However, the task still requires human oversight for ensuring data accuracy, completeness, and adherence to medical regulations, which AI cannot fully handle. The context of performing this task in a high-income country like Poland, where digital infrastructures are robust, supports a higher potential for AI assistance. Thus, the chosen score of 0.57 reflects AI's capability to significantly aid these tasks while recognizing the importance of human involvement in maintaining the nuances and accuracy required in medical documentation. The score aligns closely with other semantically similar tasks, considering the structured data nature and involvement of sensitive patient information.

Moving fastest, 2023 → 2025

“Recording information on patients' health status and responses to treatment in medical records-keeping systems, and sharing information with other health professionals as required to ensure continuing and comprehensive care;”

Model capability on this task changed by +0.26 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 2264, 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.

• Physical Therapists
• Exercise Physiologists

In context

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

Physiotherapists sit at the 53rd percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Physiotherapists rank in the 53rd 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 0.11 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Recording information on patients' health status and responses to treatment in medical records-keeping systems, and sharing information with other health professionals as required to ensure continuing and comprehensive care;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Physiotherapists". https://singulariki.com/gradient/2264-physiotherapists.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.