Fishing and hunting workers: AI exposure and career outlook
Fishing and hunting workers (SOC 45-3031) 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 10% 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.
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
- 45-3031
- Canada NOC 2021
- 83120
- TEER level
- Not available
- COPS outlook
- Not assessed
What the measurements actually say
One of three independent studies measure AI exposure for this occupation directly; the others report no coverage for it. The two percentages below them are ours, modelled from those measurements.
| Metric | Value | Provenance |
|---|---|---|
| AI applicability | 6% | Measured — Microsoft Research, from 200,000 Copilot conversations classified against O*NET work activities. |
| Observed AI usage | Not available | Not covered by Anthropic's occupation-level dataset. |
| Academic AI exposure | Not available | Not covered by the Felten AIOE table. |
| 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) | 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) | 10% | 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 83120
Fishing and hunting workers map to NOC 83120 — Fishing masters and officers. ESDC's COPS 2024–2033 projection for this unit group is not assessed.
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 Fishing and hunting workers— the work itself, as reported by people doing the job — grouped by the work activity each task belongs to. Showing 12 of 29, 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 6% of this occupation's work activities are covered by observed AI usage, but not which ones.
Handling and Moving Objects · 4 tasks
Remove catches from fishing equipment and measure them to ensure compliance with legal size.
Core task · Importance 4.6/5 (O*NET)
Select, bait, and set traps, and lay poison along trails, according to species, size, habits, and environs of birds or animals and reasons for trapping them.
Core task · Importance 4.3/5 (O*NET)
Connect accessories such as floats, weights, flags, lights, or markers to nets, lines, or traps.
Core task · Importance 4.1/5 (O*NET)
Harvest marine life for human or animal consumption, using diving or dredging equipment, traps, barges, rods, reels, or tackle.
Core task · Importance 3.9/5 (O*NET)
Operating Vehicles, Mechanized Devices, or Equipment · 3 tasks
Steer vessels and operate navigational instruments.
Core task · Importance 4.8/5 (O*NET)
Interpret weather and vessel conditions to determine appropriate responses.
Core task · Importance 4.5/5 (O*NET)
Travel on foot, by vehicle, or by equipment such as boats, snowmobiles, helicopters, snowshoes, or skis to reach hunting areas.
Core task · Importance 4.5/5 (O*NET)
Performing General Physical Activities · 2 tasks
Wash decks, conveyors, knives, and other equipment, using brushes, detergents, and water.
Core task · Importance 4.1/5 (O*NET)
Load and unload vessel equipment and supplies, by hand or using hoisting equipment.
Core task · Importance 3.4/5 (O*NET)
Guiding, Directing, and Motivating Subordinates · 2 tasks
Direct fishing or hunting operations, and supervise crew members.
Core task · Importance 4.6/5 (O*NET)
Oversee the purchase of supplies, gear, and equipment.
Core task · Importance 3.6/5 (O*NET)
Repairing and Maintaining Electronic Equipment · 1 task
Maintain engines, fishing gear, and other on-board equipment and perform minor repairs.
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 Fishing and hunting workers 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.
Obtain technical certifications in advanced diagnostic tools and smart systems relevant to fishing and hunting workers 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 fishing and hunting workers.
Sources for this occupation
Only the sources that hold data for fishing and hunting workers 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.
- 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.
- 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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