SOC 31-1131Canada NOC 33102Insulated

Nursing assistants and orderlies: AI exposure and career outlook

Nursing assistants and orderlies (SOC 31-1131) sit at the 2nd percentile for measured AI exposure among the 342 occupations tracked here, measured from a composite of Microsoft Research and Anthropic Economic Index telemetry. An estimated 3% of tasks are already automated and 9% are being reshaped rather than replaced — both modelled figures, not direct measurements. Goldman Sachs classifies AI's primary effect on this role as augments, which places it in the Insulated group: little measured AI exposure so far. No urgency here, though the tools are still worth having in your hands. In Canada the role maps to NOC 33102 (Nurse aides, orderlies and patient service associates), and ESDC's COPS 2024–2033 outlook for that unit group is strong risk of shortage.

Figures last updated 2026-06. Every number on this page is labelled measured or modelled; where a source has no coverage for this occupation, it says so rather than showing a zero.

Key facts

SOC code
31-1131
Canada NOC 2021
33102
TEER level
3 — College / Apprenticeship <2 yrs
COPS outlook
Strong risk of Shortage

What the measurements actually say

Three independent studies measure AI exposure for this occupation directly. The two percentages below them are ours, modelled from those measurements.

Measured and modelled AI exposure figures for Nursing assistants and orderlies
MetricValueProvenance
AI applicability3%Measured — Microsoft Research, from 200,000 Copilot conversations classified against O*NET work activities.
Observed AI usage0%Measured — Anthropic Economic Index, share of tasks observed being performed with Claude (CC-BY 4.0).
Academic AI exposureNot availableNot covered by the Felten AIOE table.
Estimated task automation (modelled)3%Modelled from this occupation's measured telemetry composite, mapped through anchors calibrated to Anthropic's published aggregate findings. Our estimate, not per-occupation telemetry.
Estimated task reshaping (modelled)9%Share of tasks where AI acts as co-pilot rather than replacement. Modelled from the measured telemetry composite, calibrated to BCG's published aggregate reshaping rates. Our estimate.
Exposure band: Safe

This skill domain has minimal AI substitution risk. AI is primarily augmenting — not replacing — professionals here.

In Canada: NOC 33102

Nursing assistants and orderlies map to NOC 33102Nurse aides, orderlies and patient service associates at TEER 3 (College / Apprenticeship <2 yrs). ESDC's COPS 2024–2033 projection for this unit group is Strong risk of Shortage.

Mapped via Statistics Canada's official SOC 2018 → NOC 2016 → NOC 2021 correspondence tables. TEER is derived from the official NOC code, so it cannot disagree with it.

Where the leverage is

With low AI exposure, the focus for this role is on adopting productivity tools. Leverage AI for scheduling, administrative tasks, and analytics to double operational throughput.

Physical requirements and manual dexterity provide strong natural insulation from AI substitution. AI is primarily a peripheral tool for diagnostics.

Canada transition step

Obtain technical certifications in advanced diagnostic tools and smart systems relevant to nursing assistants and orderlies to prepare for future technological integrations.

This guidance is written per exposure band — three texts across all 342 occupations, framed on the ILO's transformation-versus-displacement distinction. It is editorial guidance for the safe band, not an occupation-specific research finding about nursing assistants and orderlies.

Sources for this occupation

Only the sources that hold data for nursing assistants and orderlies are listed. A study that does not cover this occupation is not cited here.

  • Microsoft Research — Working with AI (Tomlinson et al., arXiv:2507.07935): Measured AI applicability, from 200,000 anonymised Copilot conversations classified against O*NET work activities.
  • Anthropic Economic Index: Measured observed AI usage per occupation, from Anthropic's open per-SOC dataset (CC-BY 4.0).
  • Goldman Sachs Economics: Augmentation-versus-substitution classification, from research mapping 900+ occupations (April 24, 2026).
  • Statistics Canada NOC 2021 concordance: Official SOC 2018 → NOC 2016 V1.3 → NOC 2021 V1.0 correspondence tables; TEER derived from the official code.
  • ESDC COPS 2024–2033: Projected labour-market assessment per NOC 2021 unit group, from the Canadian Occupational Projection System open dataset.
  • BCG — AI Will Reshape More Jobs Than It Replaces (April 3, 2026): Published aggregate reshaping rates, used to calibrate our modelled percentages. The per-occupation figures here are our estimates, not BCG's data.

Related occupations

Other roles in Trades & Healthcare.

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