SOC 39-7010Canada NOC 64320Displacement risk

Tour and travel guides: AI exposure and career outlook

Tour and travel guides (SOC 39-7010) sit at the 96th 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 66% of tasks are already automated and 82% are being reshaped rather than replaced — both modelled figures, not direct measurements. Of the Claude usage observed in this occupation, 67% follows an automation pattern and 33% an augmentation pattern, which places it in the Displacement risk group: the routine layer of this work is being automated outright. The judgment layer is not, so the move is to own more of it. In Canada the role maps to NOC 64320 (Tour and travel guides), and ESDC's COPS 2024–2033 outlook for that unit group is balance.

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
39-7010
Canada NOC 2021
64320
TEER level
4 — Secondary School
COPS outlook
Balance

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 Tour and travel guides
MetricValueProvenance
AI applicability32%Measured — Microsoft Research, from 200,000 Copilot conversations classified against O*NET work activities.
Observed AI usageNot availableNot covered by Anthropic's occupation-level dataset.
Academic AI exposure62nd percentileMeasured — Felten-Raj-Seamans AIOE index across 774 occupations; the index underlying Statistics Canada's Canadian estimates. Occupation-group average of 2 detailed roles.
Automation-pattern usage67%Measured — the share of observed Claude usage in this occupation where the task is handed over rather than iterated on (Anthropic Economic Index). Occupation-group average of 2 detailed roles.
Augmentation-pattern usage33%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)66%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)82%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 64320

Tour and travel guides map to NOC 64320 — Tour and travel guides at TEER 4 (Secondary School). ESDC's COPS 2024–2033 projection for this unit group is Balance.

Mapped via Statistics Canada's official SOC 2018 → NOC 2016 → NOC 2021 correspondence tables (closest match of several correspondence candidates). Several candidates were available, and this one matched the occupation title on every word — no other did — so the TEER level read off its second digit is reported.

What this job actually involves

These are the O*NET task statements for Tour and travel guides— the work itself, as reported by people doing the job — grouped by the work activity each task belongs to. Showing 12 of 36, 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.

4 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 32% of this occupation's work activities are covered by observed AI usage, but not which ones.

SOC 39-7010 is a BLS occupation group. These statements are pooled across the 2 detailed occupations in it, so a given task may apply to only some of them.

Communicating with People Outside the Organization · 2 tasks

  • Describe tour points of interest to group members, and respond to questions.

    Core task · Importance 4.9/5 (O*NET) · 43% of observed AI use on this task is automation-pattern · reported by 1 of 2 occupations in this group

  • Provide directions and other pertinent information to visitors.

    Core task · Importance 4.0/5 (O*NET) · 84% of observed AI use on this task is automation-pattern · reported by 1 of 2 occupations in this group

Assisting and Caring for Others · 2 tasks

  • Arrange for tour or expedition details such as accommodations, transportation, equipment, and the availability of medical personnel.

    Core task · Importance 4.6/5 (O*NET) · reported by 1 of 2 occupations in this group

  • Attend to special needs of tour participants.

    Core task · Importance 4.2/5 (O*NET) · reported by 1 of 2 occupations in this group

Getting Information · 1 task

  • Research various topics, including site history, environmental conditions, and clients' skills and abilities to plan appropriate expeditions, instruction, and commentary.

    Core task · Importance 4.1/5 (O*NET) · 45% of observed AI use on this task is automation-pattern · reported by 1 of 2 occupations in this group

Monitoring Processes, Materials, or Surroundings · 1 task

  • Monitor visitors' activities to ensure compliance with establishment or tour regulations and safety practices.

    Core task · Importance 4.5/5 (O*NET) · reported by 1 of 2 occupations in this group

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

  • Evaluate services received on the tour, and report findings to tour organizers.

    Core task · Importance 4.1/5 (O*NET) · reported by 1 of 2 occupations in this group

Performing General Physical Activities · 1 task

  • Escort individuals or groups on cruises, sightseeing tours, or through places of interest, such as industrial establishments, public buildings, or art galleries.

    Core task · Importance 4.6/5 (O*NET) · reported by 1 of 2 occupations in this group

Selling or Influencing Others · 1 task

  • Sell travel packages.

    Core task · Importance 4.1/5 (O*NET) · reported by 1 of 2 occupations in this group

Performing for or Working Directly with the Public · 1 task

  • Resolve any problems with itineraries, service, or accommodations.

    Core task · Importance 4.5/5 (O*NET) · 83% of observed AI use on this task is automation-pattern · reported by 1 of 2 occupations in this group

Coordinating the Work and Activities of Others · 1 task

  • Plan tour itineraries, applying knowledge of travel routes and destination sites.

    Core task · Importance 4.5/5 (O*NET) · reported by 1 of 2 occupations in this group

Training and Teaching Others · 1 task

  • Conduct educational activities for school children.

    Core task · Importance 4.2/5 (O*NET) · reported by 1 of 2 occupations in this group

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 Tour and travel guides 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 tour and travel guides.

Sources for this occupation

Only the sources that hold data for tour and travel guides 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.
  • 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.

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

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