Share and intensity of work current AI systems can materially affect.
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.
Likely potential for exposed tasks to move to software after workflow integration.
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
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.
+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.
+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.
+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.
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.
- 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
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)
Steer vessels and operate navigational instruments
Exposure 26, automation 11%, augmentation 44%.
O*NET evidence: Steer vessels and operate navigational instruments. (ID 23403)
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)
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)
Transition pathways
Adjacent moves that preserve existing skills
Fishing Vessel Captain
Training horizon: 12-24 months. Skill overlap 62. Wage preservation signal 136.
- Accumulate sea time
- Earn captain licensing
- Own vessel operations
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
Comparison guides
Compare the next move before you commit
Fishing and Hunting Workers to Fishing Vessel Captain
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Fishing and Hunting Workers into Fishing Vessel Captain.
Fishing and Hunting Workers to Mariculture Operations Lead
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Fishing and Hunting Workers into Mariculture Operations Lead.
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.
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.
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.
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.
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.
- 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.
- By 60 days, complete one small project connected to Fishing Vessel Captain, such as accumulate sea time.
- 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