SOC 25-2031Canada NOC 41220Orchestrator opportunity

High school teachers: AI exposure and career outlook

High school teachers (SOC 25-2031) sit at the 75th 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 47% of tasks are already automated and 68% are being reshaped rather than replaced — both modelled figures, not direct measurements. Of the Claude usage observed in this occupation, 42% follows an automation pattern and 58% an augmentation pattern, which places it in the Orchestrator opportunity group: AI reaches deep into this work and amplifies it. The leverage goes to whoever directs it, and that can be you. In Canada the role maps to NOC 41220 (Secondary school teachers), and ESDC's COPS 2024–2033 outlook for that unit group is moderate 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
25-2031
Canada NOC 2021
41220
TEER level
1 — University Degree
COPS outlook
Moderate 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 High school teachers
MetricValueProvenance
AI applicability18%Measured — Microsoft Research, from 200,000 Copilot conversations classified against O*NET work activities.
Observed AI usage29%Measured — Anthropic Economic Index, share of tasks observed being performed with Claude (CC-BY 4.0).
Academic AI exposure82nd percentileMeasured — Felten-Raj-Seamans AIOE index across 774 occupations; the index underlying Statistics Canada's Canadian estimates.
Automation-pattern usage42%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 usage58%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)47%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)68%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: High Risk

This skill domain faces significant AI substitution. The opportunity is in pivoting to AI orchestration and higher-order human judgment within the domain.

In Canada: NOC 41220

High school teachers map to NOC 41220 — Secondary school teachers at TEER 1 (University Degree). ESDC's COPS 2024–2033 projection for this unit group is Moderate 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 High school teachers— the work itself, as reported by people doing the job — grouped by the work activity each task belongs to. Showing 12 of 32, 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.

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 18% of this occupation's work activities are covered by observed AI usage, but not which ones.

Thinking Creatively · 4 tasks

  • Establish and enforce rules for behavior and procedures for maintaining order among students.

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

  • Establish clear objectives for all lessons, units, and projects, and communicate those objectives to students.

    Core task · Importance 3.9/5 (O*NET)

  • Plan and conduct activities for a balanced program of instruction, demonstration, and work time that provides students with opportunities to observe, question, and investigate.

    Core task · Importance 3.9/5 (O*NET)

  • Prepare objectives and outlines for courses of study, following curriculum guidelines or requirements of states and schools.

    Core task · Importance 3.9/5 (O*NET)

Documenting/Recording Information · 2 tasks

  • Adapt teaching methods and instructional materials to meet students' varying needs and interests.

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

  • Use computers, audio-visual aids, and other equipment and materials to supplement presentations.

    Core task · Importance 3.9/5 (O*NET)

Monitoring Processes, Materials, or Surroundings · 1 task

  • Observe and evaluate students' performance, behavior, social development, and physical health.

    Core task · Importance 3.9/5 (O*NET)

Judging the Qualities of Objects, Services, or People · 1 task

  • Prepare, administer, and grade tests and assignments to evaluate students' progress.

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

Handling and Moving Objects · 1 task

  • Prepare materials and classrooms for class activities.

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

Developing and Building Teams · 1 task

  • Prepare students for later grades by encouraging them to explore learning opportunities and to persevere with challenging tasks.

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

Training and Teaching Others · 1 task

  • Instruct through lectures, discussions, and demonstrations in one or more subjects, such as English, mathematics, or social studies.

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

Providing Consultation and Advice to Others · 1 task

  • Guide and counsel students with adjustments, academic problems, or special academic interests.

    Core task · Importance 3.9/5 (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 High school teachers 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

Transition to high-value advisory, complex case analysis, or AI system oversight. The pivot is to move from routine execution to AI orchestration and quality assurance.

Cognitive, information-based tasks are highly exposed. Entry-level displacement pressure is high, necessitating transition to advisory and governance roles.

Canada transition step

Master workflow automation platforms (e.g., Make, Zapier, CRM integrations) to double your output and position for fractional leadership roles.

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 high risk band, not an occupation-specific research finding about high school teachers.

Sources for this occupation

Only the sources that hold data for high school teachers 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).
  • Felten, Raj & Seamans — AI Occupational Exposure index: Measured academic exposure percentile; the index underlying Statistics Canada's Canadian AI-exposure estimates (Mehdi & Morissette, 2024).
  • 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.

Related occupations

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

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