SOC 45-3031

Fishing and Hunting Workers AI displacement risk

Fishing and hunting workers catch fish and trap game using vessels, nets, and traps. Sonar and fish-finding electronics improve location, but hauling nets in weather, maintaining gear at sea, and reading conditions are physical work — and quota management, not automation, determines how much fishing happens.

Exposure26

Share and intensity of work current AI systems can materially affect.

Automation10%

Likely potential for exposed tasks to move to software after workflow integration.

Risk bandLow

The occupation's risks and limits are regulatory and environmental: catch shares and stock assessments set the economics. Technology assists navigation and finding; it does not haul the net.

Distribution

Where Fishing and Hunting Workers sits across 620 tracked roles

Fishing and Hunting Workers · 12050100

Displacement pressure 12 — higher than 2% of the 620 occupations tracked on displacement.ai.

Score version

This page uses Seed model v0.4 (seed-v0.4-2026-05), last reviewed 2026-08-15. Directional occupation-level planning model using hand-reviewed public research, task exposure estimates, wage context, and transition-pathway assumptions.

29 O*NET task statements matched to SOC 45-3031. The displayed task profile combines these official task statements with the current public score model.

Median wage context: $40,800 (Fallback estimate; May 2025 median unavailable, US national). BLS does not publish an exact current median for this occupational split, so the page retains a clearly labeled fallback estimate.

Scores are planning signals, not forecasts. Local hiring demand, employer-specific workflows, licensing, and credentials must be validated before making career decisions.

2030 economic stress test

How Anthropic's scenarios classify Fishing and Hunting Workers

SOC 45-3031 places this role in the paper's all-other occupation group. These group-level outcomes do not change the 12/100 role score and are not an occupation forecast.

Modest change

+1.1% group wage

Employment rises and unemployment falls for the all-other group, but the paper does not publish a separate group rate.

Economy-wide: +1.6% GDP and 3.9% unemployment.

Substantial change

+5.9% group wage

Employment rises and unemployment falls for the all-other group, but the paper does not publish a separate group rate.

Economy-wide: +8.3% GDP and 4.6% unemployment.

Extreme change

+33.6% group wage

Employment rises and unemployment falls for the all-other group, but the paper does not publish a separate group rate.

Economy-wide: +32.4% GDP and 11.9% unemployment.

Compare the assumptions and limitations across all three scenarios. Source: The Anthropic Institute Working Paper No. 2026-02.

Official task evidence

O*NET task matches for Fishing and Hunting Workers

The current evidence import matched 29 task statements from Task Statements 31.0 (August 2026). These rows are used as a grounding layer for judging which parts of the occupation are repeatable, language-heavy, analytical, social, physical, or compliance-sensitive.

Dataset31.0 (August 2026)
Matched tasks29
SOC45-3031
  • Core task / ID 23403

    Steer vessels and operate navigational instruments.

  • Core task / ID 23410

    Remove catches from fishing equipment and measure them to ensure compliance with legal size.

  • Core task / ID 23428

    Direct fishing or hunting operations, and supervise crew members.

  • Core task / ID 23419

    Interpret weather and vessel conditions to determine appropriate responses.

  • Core task / ID 23402

    Travel on foot, by vehicle, or by equipment such as boats, snowmobiles, helicopters, snowshoes, or skis to reach hunting areas.

  • Core task / ID 23415

    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.

Source: O*NET Resource Center, Task Statements. Raw import target: data/raw/onet/task-statements-31-0.txt.

Task profile

Where AI changes the work

physical

Remove catches from equipment and measure for compliance

Exposure 18, automation 7%, augmentation 34%.

O*NET evidence: Remove catches from fishing equipment and measure them to ensure compliance with legal ... (ID 23410)

technical

Steer vessels and operate navigational instruments

Exposure 26, automation 11%, augmentation 44%.

O*NET evidence: Steer vessels and operate navigational instruments. (ID 23403)

analytical

Interpret weather and vessel conditions for response

Exposure 24, automation 9%, augmentation 48%.

O*NET evidence: Interpret weather and vessel conditions to determine appropriate responses. (ID 23419)

physical

Maintain engines, gear, and on-board equipment

Exposure 20, automation 8%, augmentation 38%.

O*NET evidence: Maintain engines, fishing gear, and other on-board equipment and perform minor repairs. (ID 23408)

TaskExposureAutomationAugmentation
Remove catches from equipment and measure for compliance187%34%
Steer vessels and operate navigational instruments2611%44%
Interpret weather and vessel conditions for response249%48%
Maintain engines, gear, and on-board equipment208%38%

Transition pathways

Adjacent moves that preserve existing skills

credentialed transition

Fishing Vessel Captain

Training horizon: 12-24 months. Skill overlap 62. Wage preservation signal 136.

  • Accumulate sea time
  • Earn captain licensing
  • Own vessel operations
Low
role redesign

Mariculture Operations Lead

Training horizon: 6-12 months. Skill overlap 58. Wage preservation signal 116.

  • Move into aquaculture
  • Manage farmed-stock cycles
  • Run feeding and health systems
Low

Comparison guides

Compare the next move before you commit

What the AI risk score means for Fishing and Hunting Workers

The displacement pressure score for Fishing and Hunting Workers is 12. That score blends task exposure, automation pressure, augmentation potential, wage vulnerability, transition feasibility, and source confidence. It is designed to help workers and workforce teams decide where to act first, not to claim a specific date when a job will disappear.

For this role, the clearest risk pattern is visible at the task level. Steer vessels and operate navigational instruments carries 11% automation pressure, while Interpret weather and vessel conditions for response carries 48% augmentation potential. That means the best response is usually a targeted redesign of work: move away from repeatable production tasks and toward judgment, exception handling, coordination, stakeholder context, and accountable use of AI tools.

Labor-market context and wage risk

Median wage: $40,800 (Fallback estimate; May 2025 median unavailable, US national). Employment context: Commercial fishing — physical, dangerous, and quota-driven. Typical education: No formal credential; licensing and safety training required.

Wage vulnerability is 58, while transition feasibility is 56. A high wage-vulnerability score means workers should pay close attention to salary preservation before making a move. A high transition-feasibility score means there are adjacent paths that can reuse existing skills without requiring a complete career reset.

  • Low displacement pressure
  • Quotas, not automation, set the economics
  • Deck work stays dangerous and human

Upskilling priorities

Skills that make this role more resilient

The safest upskilling plan starts with skills already close to the work. For Fishing and Hunting Workers, the strongest near-term skill priorities are listed below. These are useful whether the goal is to stay in the role, move to a redesigned version of the role, or transition into an adjacent occupation.

Priority 1

Vessel operations

Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.

Priority 2

Gear handling

Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.

Priority 3

Weather judgment

Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.

Priority 4

Catch compliance

Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.

90-day transition plan

The most practical next step is not to wait for a layoff or a full role redesign. Use the next 90 days to create evidence that you can operate in a safer, more AI-augmented version of the work.

  1. In the first 30 days, document the repetitive tasks in your current work and identify where AI can reduce drafting, lookup, classification, or reporting time.
  2. By 60 days, complete one small project connected to Fishing Vessel Captain, such as accumulate sea time.
  3. By 90 days, compare internal openings and external postings for Fishing Vessel Captain or Mariculture Operations Lead and update your resume around measurable workflow outcomes.

FAQ

Questions about AI and Fishing and Hunting Workers

Will AI replace Fishing and Hunting Workers?

Fishing and hunting workers catch fish and trap game using vessels, nets, and traps. Sonar and fish-finding electronics improve location, but hauling nets in weather, maintaining gear at sea, and reading conditions are physical work — and quota management, not automation, determines how much fishing happens. The better planning signal is not full replacement, but which tasks become automated, which tasks become AI-assisted, and which responsibilities still need human judgment.

Which parts of Fishing and Hunting Workers work are most exposed to AI?

Steer vessels and operate navigational instruments and Interpret weather and vessel conditions for response show the strongest automation pressure in this model. Interpret weather and vessel conditions for response and Steer vessels and operate navigational instruments are better treated as AI-augmented work.

What should Fishing and Hunting Workers learn next?

Start with Vessel operations, Gear handling, Weather judgment. The most practical adjacent paths in this model are Fishing Vessel Captain and Mariculture Operations Lead.

How should this score be used?

Use it as a planning signal, not a prediction. Confirm local hiring demand, wages, licensing, credentials, and employer adoption before making a career move.

Sources

Evidence trail