SOC 31-1133Canada NOC 33102Insulated

Psychiatric technicians and aides: AI exposure and career outlook

Psychiatric technicians and aides (SOC 31-1133) sit at the 11th 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 7% of tasks are already automated and 18% are being reshaped rather than replaced — both modelled figures, not direct measurements. Of the Claude usage observed in this occupation, 86% follows an automation pattern and 14% an augmentation pattern, 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
31-1133
Canada NOC 2021
33102
TEER level
3 — College / Apprenticeship <2 yrs
COPS outlook
Strong risk of Shortage

What the measurements actually say

Two of three independent studies measure AI exposure for this occupation directly; the other reports no coverage for it. The two percentages below them are ours, modelled from those measurements.

Measured and modelled AI exposure figures for Psychiatric technicians and aides
MetricValueProvenance
AI applicability7%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.
Automation-pattern usage86%Measured — the share of observed Claude usage in this occupation where the task is handed over rather than iterated on (Anthropic Economic Index).
Augmentation-pattern usage14%Measured — the complement of the row above; the two sum to 100% by construction. This is the pattern where the person stays in the loop.
Estimated task automation (modelled)7%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)18%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

Psychiatric technicians and aides map to NOC 33102 — Nurse 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 the second digit of the official NOC code, so it cannot disagree with it.

What this job actually involves

These are the O*NET task statements for Psychiatric technicians and aides— the work itself, as reported by people doing the job — grouped by the work activity each task belongs to. Showing 12 of 17, core tasks first.

The exposure figures above are for the occupation as a whole. We do not have a per-task measurement: no published dataset tells us which of these specific tasks AI is doing. Read this as what the job is made of, not as a ranking of what is at risk.

1 of these 12statements do carry one measured signal: Anthropic publishes, per O*NET task, how much of the observed Claude usage on it looked like automation rather than iteration. Those are marked below. It still says how people use AI on that task, not how much of it AI can do — and the unmarked statements carry nothing rather than inheriting the occupation's figure.

Microsoft's applicability score was itself produced by classifying Copilot conversations against the O*NET work-activity catalogue — the same catalogue these groups come from. The published file gives one number per occupation, not one per activity, so we can tell you that 7% of this occupation's work activities are covered by observed AI usage, but not which ones.

Assisting and Caring for Others · 5 tasks

  • Provide patients with cognitive, intellectual, or developmental disabilities with routine physical, emotional, psychological, or rehabilitation care under the direction of nursing or medical staff.

    Core task · Importance 4.6/5 (O*NET)

  • Restrain or aid patients as necessary to prevent injury.

    Core task · Importance 4.4/5 (O*NET)

  • Provide patients with assistance in bathing, dressing, or grooming, demonstrating these skills as necessary.

    Core task · Importance 4.2/5 (O*NET)

  • Aid patients in becoming accustomed to hospital routines.

    Core task · Importance 4.2/5 (O*NET)

  • Serve meals or feed patients needing assistance or persuasion.

    Core task · Importance 4.2/5 (O*NET)

Developing and Building Teams · 2 tasks

  • Listen and provide emotional support and encouragement to psychiatric patients.

    Core task · Importance 4.6/5 (O*NET)

  • Organize, supervise, or encourage patient participation in social, educational, or recreational activities.

    Core task · Importance 4.2/5 (O*NET)

Monitoring Processes, Materials, or Surroundings · 1 task

  • Complete physical checks and monitor patients to detect unusual or harmful behavior and report observations to professional staff.

    Core task · Importance 4.5/5 (O*NET)

Evaluating Information to Determine Compliance with Standards · 1 task

  • Maintain patients' restrictions to assigned areas.

    Core task · Importance 4.3/5 (O*NET)

Performing General Physical Activities · 1 task

  • Clean and disinfect rooms and furnishings to maintain a safe and orderly environment.

    Core task · Importance 4.1/5 (O*NET)

Documenting/Recording Information · 1 task

  • Record and maintain patient information, such as vital signs, eating habits, behavior, progress notes, treatments, or discharge plans.

    Core task · Importance 4.3/5 (O*NET) · 88% of observed AI use on this task is automation-pattern

Communicating with Supervisors, Peers, or Subordinates · 1 task

  • Work as part of a team that may include psychiatrists, psychologists, psychiatric nurses, or social workers.

    Core task · Importance 4.3/5 (O*NET)

Task statements and work activities from the O*NET Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA), used under CC BY 4.0. O*NET® is a trademark of USDOL/ETA. USDOL/ETA has not reviewed or approved this material.

That's the average. Is this you?

Everything above describes Psychiatric technicians and aides as a whole. Three questions, and nothing is stored or sent.

Where are you in your career?

What does your week mostly look like?

Is your employer deploying AI?

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 psychiatric technicians and aides 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 psychiatric technicians and aides.

Sources for this occupation

Only the sources that hold data for psychiatric technicians and aides 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).
  • O*NET Database 31.0 (USDOL/ETA), CC BY 4.0: The occupation's task statements and work activities, verbatim. Joined on SOC 2018 with no crosswalk — O*NET-SOC is built on SOC — and carrying no claim about which tasks AI touches.
  • Anthropic Economic Index — collaboration split (release 2026-06-26, CC-BY 4.0): Measured share of observed Claude usage following an automation rather than an augmentation pattern. This is the second axis of the grouping above.
  • Statistics Canada NOC 2021 concordance: Official SOC 2018 → NOC 2016 V1.3 → NOC 2021 V1.0 correspondence tables. TEER is the second digit of the resolved code, so we report it only where the concordance gave a single candidate.
  • 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.

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This is the picture for the role. What about your skills?

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