Paramedical Practitioners

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 9 task statements that define Paramedical Practitioners (ISCO-08 2240) score an average of 0.23 on a 0–1 exposure scale — more exposed than about 42% 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 9 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Reporting births, deaths and notifiable diseases to government authorities to meet legal and professional reporting requirements.”

Scores 0.51 on the 2025 scale. The task of reporting births, deaths, and notifiable diseases to government authorities involves structured data collection, compliance with legal reporting standards, and ensuring accurate and timely communication with the authorities. Generative AI can assist in automating parts of this process by organizing data, generating standardized reports, and ensuring that all required fields are completed based on inputs. However, due to the task's reliance on accurate initial data entry, understanding of complex regulatory frameworks, and the necessity to handle sensitive information with precision, full automation is not feasible. Similar to other documentation-heavy tasks such as maintaining patient records (automation score: 0.375) and conveying patient information in healthcare settings (automation score: 0.35), this task requires substantial human oversight to ensure accuracy, regulatory compliance, and nuanced judgment. Additionally, the need for rapid adaptation to changing regulations and the sensitivity of personal information align this task more closely with those that have moderately higher automation potential due to structured documentation needs. Considering these factors and the environment in a high-income country like Poland, an adjusted score of 0.36 is appropriate, reflecting AI's ability to assist significantly but acknowledging the indispensable human role.

Moving fastest, 2023 → 2025

“Identifying and referring complex or unusual cases to medical doctors, hospitals or other places for specialized care;”

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 2240, 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.

• Physician Assistants
• Anesthesiologist Assistants

In context

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

Paramedical Practitioners sit at the 42nd percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Paramedical Practitioners rank in the 42nd 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 0.00 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Reporting births, deaths and notifiable diseases to government authorities to meet legal and professional reporting requirements.". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Paramedical Practitioners". https://singulariki.com/gradient/2240-paramedical-practitioners.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.