Airline and commercial pilots: AI exposure and career outlook
Airline and commercial pilots (SOC 53-2010) sit at the 24th 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 13% of tasks are already automated and 29% are being reshaped rather than replaced — both modelled figures, not direct measurements. 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 72600 (Air pilots, flight engineers and flying instructors), 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
- 53-2010
- Canada NOC 2021
- 72600
- TEER level
- Not available
- 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.
| Metric | Value | Provenance |
|---|---|---|
| AI applicability | 13% | Measured — Microsoft Research, from 200,000 Copilot conversations classified against O*NET work activities. Occupation-group average of 2 detailed roles. |
| Observed AI usage | 0% | Measured — Anthropic Economic Index, share of tasks observed being performed with Claude (CC-BY 4.0). Occupation-group average of 2 detailed roles. |
| Academic AI exposure | 46th percentile | Measured — 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 usage | Not available | Not covered by Anthropic's collaboration-mode dataset. |
| Augmentation-pattern usage | Not available | Not covered by Anthropic's collaboration-mode dataset. |
| Estimated task automation (modelled) | 13% | 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) | 29% | 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. |
This skill domain has minimal AI substitution risk. AI is primarily augmenting — not replacing — professionals here.
In Canada: NOC 72600
Airline and commercial pilots map to NOC 72600 — Air pilots, flight engineers and flying instructors. 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 (closest match of several correspondence candidates). TEER is the second digit of the NOC code, so it is only as certain as the code is. Several correspondence candidates were available here and we took the closest by title, so we do not report a TEER level for it.
What this job actually involves
These are the O*NET task statements for Airline and commercial pilots— the work itself, as reported by people doing the job — grouped by the work activity each task belongs to. Showing 12 of 42, 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 13% of this occupation's work activities are covered by observed AI usage, but not which ones.
SOC 53-2010 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.
Operating Vehicles, Mechanized Devices, or Equipment · 5 tasks
Co-pilot aircraft or perform captain's duties, as required.
Core task · Importance 4.9/5 (O*NET) · reported by 1 of 2 occupations in this group
Use instrumentation to guide flights when visibility is poor.
Core task · Importance 4.9/5 (O*NET) · reported by 1 of 2 occupations in this group
Use instrumentation to pilot aircraft when visibility is poor.
Core task · Importance 4.9/5 (O*NET) · reported by 1 of 2 occupations in this group
Start engines, operate controls, and pilot airplanes to transport passengers, mail, or freight, adhering to flight plans, regulations, and procedures.
Core task · Importance 4.9/5 (O*NET) · reported by 1 of 2 occupations in this group
Work as part of a flight team with other crew members, especially during takeoffs and landings.
Core task · Importance 4.9/5 (O*NET) · reported by 1 of 2 occupations in this group
Inspecting Equipment, Structures, or Materials · 2 tasks
Check aircraft prior to flights to ensure that the engines, controls, instruments, and other systems are functioning properly.
Core task · Importance 5.0/5 (O*NET) · reported by 1 of 2 occupations in this group
Inspect aircraft for defects and malfunctions, according to pre-flight checklists.
Core task · Importance 4.8/5 (O*NET) · reported by 1 of 2 occupations in this group
Communicating with Supervisors, Peers, or Subordinates · 2 tasks
Respond to and report in-flight emergencies and malfunctions.
Core task · Importance 4.9/5 (O*NET) · reported by 1 of 2 occupations in this group
Contact control towers for takeoff clearances, arrival instructions, and other information, using radio equipment.
Core task · Importance 4.8/5 (O*NET)
Monitoring Processes, Materials, or Surroundings · 1 task
Monitor engine operation, fuel consumption, and functioning of aircraft systems during flights.
Core task · Importance 4.8/5 (O*NET)
Making Decisions and Solving Problems · 1 task
Consider airport altitudes, outside temperatures, plane weights, and wind speeds and directions to calculate the speed needed to become airborne.
Core task · Importance 4.9/5 (O*NET) · reported by 1 of 2 occupations in this group
Resolving Conflicts and Negotiating with Others · 1 task
Order changes in fuel supplies, loads, routes, or schedules to ensure safety of flights.
Core task · Importance 4.8/5 (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 Airline and commercial pilots 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.
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 safe band, not an occupation-specific research finding about airline and commercial pilots.
Sources for this occupation
Only the sources that hold data for airline and commercial pilots 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.
- 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
Other roles in Management & Ops.
This is the picture for the role. What about your skills?
These numbers describe an occupation, not a person. Map your own skills against them, see which pathways stay open, and plan the transition you actually want.