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Will AI replace fishing and hunting workers?

Nah.

Most of the work is physical and outdoors: setting and hauling gear, handling catch and animals, and fixing equipment on the spot. This job scores 84 out of 100 on (higher is safer). Today people do 15% of the work with AI’s help, and 85% still needs a person.

Updated 3 October 2026 45-3031 5119 2026-Q4
Farming, Fishing, and ForestryFishing and Hunting Workers45-3031 · 2026-Q4
0% AI does it15% AI helps85% needs a human
Your job's name, lit by the work that still needs a human.Needs a human 85%AI helps 15%AI does it 0%

AI does it: AI can do the task largely by itself. AI helps: a person still does it, faster with AI. Needs a human: AI can do little of it yet.

Why the deck, not the desk, decides this one

The short answer: will AI replace hunting workers and commercial fishers? Not in the way the question usually implies. Most of this job happens on a moving boat, in brush, or at a gutting table. Setting and hauling gear, untangling a net, cleaning and icing a catch, tracking and handling game, fixing a winch when the weather turns — that work needs hands, balance and judgment in the same place at the same time.

Our figures put 85% of task time in the group that still needs a person. That is not a claim about skill. It is a claim about where the work sits. Software can read a sonar return. It cannot stand in a swell and decide the set is wrong.

The second reason is variety. Two trips are rarely alike. Tides, stock, ice, fuel, permits and crew all move at once. Systems that automate well tend to repeat a stable task thousands of times. This job repeats a pattern, not a task.

What software handles, what it assists, and what it leaves

The group marked as something AI can do covers 0% of task time. These are the clerical edges: keeping logs of catch weights and locations, and filing the reports that licenses and quotas require. That paperwork moved to apps and electronic reporting systems long before anyone called it AI.

The assist group is 15% of task time. This is where the real change is happening. Sonar and chartplotters narrow where to look. Weather models shape whether to sail. Camera and sensor systems help monitor gear and bycatch. The decision stays with the skipper and crew; the information gets better. Overall coverage — our estimate of task time AI can handle today — sits at 8 out of 100. The coverage method page explains how that is built.

Everything else stays with people: the physical handling of gear and animals, the repairs made at sea with what is on board, and the calls about when to stop. Those tasks are the bulk of the day.

Good to know: better fish-finding technology can raise the catch per trip without reducing the number of hands needed to work the gear.

How strong is the evidence?

Thin, and we say so. Our evidence grade for quality parity here is D. That bottom grade means one thing: nobody has tested a machine against a working fisher or hunter on these tasks, so we give no parity number at all. Guessing one would be worse than leaving it blank.

What would settle it is specific. A timed trial of an uncrewed vessel setting, hauling and clearing a net in open water. A robot sorting and dressing a mixed catch at commercial speed. A field test of autonomous gear recovery in bad conditions. Until something like that is published, the honest position is “not measured.” Our quality parity method sets out how grades A to D are assigned, and the full approach is on the methodology page.

Official projections point a different way from the automation story. The Bureau of Labor Statistics projects employment in this occupation falling about 4.2% between 2025 and 2035 (BLS, 2025). The usual pressures behind that are stock limits, fuel and vessel costs, consolidation and quota rules — not software.

When this could change

Most likely after 2046 (8 in 10 of our scenarios). For what that window measures and how it is built, see the replacement-year method.

Two things could pull it earlier. First, uncrewed and lightly crewed vessels moving from research and survey work into commercial harvesting, with deck machinery that sets and retrieves gear on its own. Second, a real drop in the price of dexterous mobile robots that can work wet, cold and tilting surfaces — the hardware class this job would need, covered in our guide to humanoid robots and physical jobs.

Two things hold it back. Marine-grade equipment is expensive to buy, insure and maintain, and salt water destroys anything delicate; most vessels are small businesses with thin margins. And the regulatory side — licensing, observer requirements, safety rules and the limits on who may take a wild animal — assumes a responsible person is present. Changing that takes legislatures, not model releases.

How to stay needed in this job

Lean into the parts that do not move. Gear work and repair: being the crew member who can splice, weld, patch and get a winch running again. Catch handling and quality: bleeding, icing and grading so the product earns a premium. Judgment at sea: reading conditions, choosing grounds and calling off a trip before it becomes a rescue.

Two skills pay off alongside those. One is electronics literacy — getting real value out of sonar, plotters, electronic logbooks and monitoring cameras rather than tolerating them. The other is the licensing and business side: permits, quota, cost control and direct sales. That is how deckhands become owners.

Nearby work worth looking at, if you want more stability or a shore-based route:

Our headline figure for this occupation is 84 out of 100 (higher is safer). To see where that sits against the rest of the field, browse the farming, fishing and forestry family, the agriculture sector, or the list of jobs that mostly need a person. You can also put this job next to another on the compare page.

Frequently asked questions

Will AI replace hunting workers and commercial fishers?

Not as whole jobs, on the evidence available. The task split above shows most of the work sitting in the group that needs a person: handling gear, working animals and catch by hand, and making calls in changing conditions. What is changing is the information layer around the work. Expect better fish-finding, better weather calls and electronic reporting, not an empty deck.

Which jobs are most likely to survive AI?

There is no fixed list of three or five. On our data, the jobs holding up best tend to combine three things: physical work in unpredictable places, direct responsibility for people or animals, and licensing that assumes a human is present. Skilled trades, hands-on care, emergency response and outdoor resource work all fit that pattern. The rankings page lets you check any job yourself.

What jobs will be gone by 2030 due to AI?

We do not publish claims that a job will be gone. The pattern in the data is task erosion and fewer entry-level openings, mostly in work done at a screen with text, numbers or scripts. Even in exposed occupations, duties shift before headcount does. The replacement-year chart on this page shows a dated range with uncertainty, not a single date.

How is technology already used in commercial fishing?

Widely, and for decades. Sonar and echo sounders locate fish. GPS and chartplotters mark grounds and gear. Net monitors report depth and spread. Electronic logbooks file catch reports to regulators. Onboard cameras support observer and bycatch monitoring. Newer systems add pattern recognition to sonar returns and camera footage. All of it informs the crew; none of it sets or hauls the gear by itself.

Is hunting declining in popularity?

Participation has shifted over the past few decades, with changes varying a lot by state and by species. The most reliable measures are hunting license sales published by state wildlife agencies and federal survey data on hunting and wildlife-watching. Check those directly rather than general commentary, because regional trends often run opposite to the national picture.

Could robots take over deck work on fishing vessels?

Some deck machinery is already automated, such as power blocks and hauling winches. Full robotic deck work is harder. The surface moves, the equipment is wet and salted, loads are irregular and repairs happen at sea. That calls for dexterous, rugged mobile machines that remain expensive. The blockers and robotics sections above show how physical the task mix is.

Each ridge is a slice of the job's task time.Needs a human 85%AI helps 15%AI does it 0%
The job’s mark

No two jobs leave the same print

Every job gets its own fingerprint, drawn from its code. The amber ridges are the share of task time that still needs a person. Below them, the same ridges are written out in ones and zeros: slate for the work AI helps with, white for the work AI can do.

Fishing and Hunting Workers, O*NET-SOC 45-3031. 85% of the job’s task time still needs a human, so 85 of every 100 ridges are amber; slate is what AI helps with, white what AI can do.

What AI can and cannot do

The tasks that make up the job, from , and where AI stands on each today: , (a person does it, with AI speeding it up) or . 85% of the still needs a human.

Each block is one task; its height is its share of working time.Needs a human 85%AI helps 15%AI does it 0%
The job's task list: the parts AI can do are blacked out.Needs a human 85%AI helps 15%AI does it 0%
Steer vessels and operate navigational instruments.Needs a human
Remove catches from fishing equipment and measure them to ensure compliance with legal size.Needs a human
Direct fishing or hunting operations, and supervise crew members.Needs a human
Interpret weather and vessel conditions to determine appropriate responses.AI helps
Travel on foot, by vehicle, or by equipment such as boats, snowmobiles, helicopters, snowshoes, or skis to reach hunting areas.Needs a human
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.Needs a human
Maintain engines, fishing gear, and other on-board equipment and perform minor repairs.Needs a human
Connect accessories such as floats, weights, flags, lights, or markers to nets, lines, or traps.Needs a human
Wash decks, conveyors, knives, and other equipment, using brushes, detergents, and water.Needs a human
Harvest marine life for human or animal consumption, using diving or dredging equipment, traps, barges, rods, reels, or tackle.Needs a human
Oversee the purchase of supplies, gear, and equipment.AI helps
Load and unload vessel equipment and supplies, by hand or using hoisting equipment.Needs a human
Scrape fat, blubber, or flesh from skin sides of pelts with knives or hand scrapers.Needs a human
Patrol trap lines or nets to inspect settings, remove catch, and reset or relocate traps.Needs a human
Locate fish, using fish-finding equipment.Needs a human
Kill or stun trapped quarry, using clubs, poisons, guns, or drowning methods.Needs a human
Maintain and repair trapping equipment.Needs a human
Obtain permission from landowners to hunt or trap on their land.AI helps
Put fishing equipment into the water and anchor or tow equipment, according to the fishing method used.Needs a human
Compute positions and plot courses on charts to navigate vessels, using instruments such as compasses, sextants, and charts.AI helps
Sort, pack, and store catch in holds with salt and ice.Needs a human
Obtain required approvals for using poisons or traps, and notify persons in areas where traps and poison are set.AI helps
Track animals by checking for signs such as droppings or destruction of vegetation.Needs a human
Skin quarry, using knives, and stretch pelts on frames to be cured.Needs a human
Transport fish to processing plants or to buyers.Needs a human
Attach nets, slings, hooks, blades, or lifting devices to cables, booms, hoists, or dredges.Needs a human
Teach or guide individuals or groups unfamiliar with specific hunting methods or types of prey.Needs a human
Release quarry from traps or nets and transfer to cages.Needs a human
Participate in animal damage control, wildlife management, disease control, and research activities.Needs a human

Is it better than a person? The evidence

No direct test against people in this job yet. Every study is , and vendor studies are labelled as such.

When could it be replaced?

When AI could largely do this job: no sooner than 2046

Most likely after 2046 (8 in 10 of our scenarios). A range from our of how fast AI improves, how fast employers take it up and what holds it back, not a forecast that the job ends. “” has a strict meaning here. Today’s answer is at the top of the page; this is how it could change.

The sand is the human working years left, measured in the same 40-year glass for every job, so a safe trade starts nearly full and an exposed job with a thin layer.

The sand is the human working years left, in the same 40-year glass for every job.Years still needing a humanYears run out

How this job could shift, year by year

Where the job could sit on our scale each year to 2060, across the ten behind its .

Today
Will AI replace this job?
Nah.
By 2045
20%
of our scenarios have AI largely doing this job by 2045 (Largely.)
10% still have it mostly needing a person (A little. or Nah.)
By 2060
80%
of our scenarios have AI largely doing this job by 2060 (Largely.)
10% still have it mostly needing a person (A little. or Nah.)

We run this job as ten scenarios spread across its replacement range. In each, the score moves towards the bottom band (Largely: AI could largely do the job) by the year that scenario reaches it, slowly at first and faster later, as adoption usually goes. Each bar splits the ten by the band they put the job in. The model stops at 2060. How the timeline works

Share of this job's scenarios in each verdict band, today to 20600%25%50%75%100%2026: 100.0% of scenarios: this job mostly needs a person (Nah.)100%Today2030: 70.0% of scenarios: this job mostly needs a person (Nah.)70%2030: 30.0% of scenarios: AI could do a little of this job (A little.)30%20302035: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2035: 70.0% of scenarios: AI could do a little of this job (A little.)70%2035: 20.0% of scenarios: AI could partly do this job (Partly.)20%20352040: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2040: 30.0% of scenarios: AI could do a little of this job (A little.)30%2040: 40.0% of scenarios: AI could partly do this job (Partly.)40%2040: 20.0% of scenarios: AI could mostly do this job (Mostly.)20%20402045: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2045: 40.0% of scenarios: AI could partly do this job (Partly.)40%2045: 30.0% of scenarios: AI could mostly do this job (Mostly.)30%2045: 20.0% of scenarios: AI could largely do this job (Largely.)20%20452050: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2050: 10.0% of scenarios: AI could partly do this job (Partly.)10%2050: 40.0% of scenarios: AI could mostly do this job (Mostly.)40%2050: 40.0% of scenarios: AI could largely do this job (Largely.)40%20502055: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2055: 30.0% of scenarios: AI could mostly do this job (Mostly.)30%2055: 60.0% of scenarios: AI could largely do this job (Largely.)60%20552060: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2060: 10.0% of scenarios: AI could mostly do this job (Mostly.)10%2060: 80.0% of scenarios: AI could largely do this job (Largely.)80%2060
Will AI replace the job?Largely.Mostly.Partly.A little.Nah.
Share of this job's scenarios in each band, year by year. Updated with every release.
Show the data
YearLargelyMostlyPartlyA littleNah
Today (2026)0.0%0.0%0.0%0.0%100.0%
20300.0%0.0%0.0%30.0%70.0%
20350.0%0.0%20.0%70.0%10.0%
20400.0%20.0%40.0%30.0%10.0%
204520.0%30.0%40.0%0.0%10.0%
205040.0%40.0%10.0%0.0%10.0%
205560.0%30.0%0.0%0.0%10.0%
206080.0%10.0%0.0%0.0%10.0%

What’s stopping AI taking over?

The things that keep this work with people, strongest first. Each is scored 0 to 100 from work context, licensing and the evidence we have.

LiabilityMistakes are rated 3.3 out of 5 for consequence and decisions 3.5 out of 5 for impact; someone has to answer for them.
Evidence gapNo study yet compares AI with people doing this job, so employers have no proof it is good enough.
Clients want a personFace-to-face contact is rated 4.4 and physical closeness 3.6 out of 5; caring for or serving people is 2.9 out of 5 in importance.
Physical work74% of the task time is physical; robots have been shown on 44% of that time.
RegulationWorkers rate responsibility for others' health and safety 3.4 out of 5.
LicensingUsual entry requirement (BLS): no formal educational credential, then moderate-term on-the-job training.

What would it cost to hand the work to AI?

The share of the year AI could handle (162 of 2,080 hours a year), priced two ways. Both are ranges, not quotes.

AI model usage, a year
$20–$1,620
A person’s wage for the same hours

AI cost covers model usage only: no integration, licences, oversight or the human time still needed to review the work. Human cost is the wage for the same hours, without benefits or overheads. As of 2026-10.

Robots and humanoids

AI software can only take the work at a screen. The rest needs a robot that can do it.

74%
of the task time is physical work
Dexterous humanoid
the kind of robot the physical work would need
Not commercial: no cited robot does most of this work; humanoids are at demonstration and pilot stage.

Source: Anthropic Economic Index, 'What work can robots do?' (30 September 2026); O*NET 31.0 task weights.

Which AI skills does this job lean on?

The job’s task time split by what an AI model would need to be good at, and where models stand today.

Each star is a task, grouped by the AI skill it leans on.Needs a human 85%AI helps 15%AI does it 0%
Writing · 4.7% of time
Strong
Drafts, edits and translates most routine documents at professional quality.
Analysis · 10.7% of time
Strong
Reliable on structured data and rules; uneven on judgement calls with thin information.
Coding · 0% of time
Strong
Agents complete many routine software tasks end to end; larger systems still need people.
Vision and design · 4.4% of time
Good
Reads documents, images and layouts well; specialist imaging needs dedicated, approved tools.
Speech · 0% of time
Good
Voice agents handle routine calls and live interpreting; complex or sensitive calls still go to people.
Planning and agents · 2.1% of time
Emerging
Multi-step agents work in narrow, well-tooled workflows; open-ended coordination is unreliable.
Physical manipulation · 71.6% of time
Early
Robots handle structured, repetitive handling; general dexterity outside fixed settings is not commercial.
Care and persuasion · 6.4% of time
Limited
Can script, coach and advise; trust, presence and accountability still need a person.
Amber matter holds its orbit, slate circles the inner disc, white falls in.Needs a human 85%AI helps 15%AI does it 0%
How exposed is it?

Still needs a human: 84/100↑ safer

The amber matter on the outside holds its orbit: that is the task time that still needs a person. The slate matter circling the inner disc is the work AI helps with. The white matter is the share AI can do; it spirals in and is gone over the edge.

The matter follows the job’s task split: 85% needs a human, 15% AI helps, 0% AI does it. Still needs a human: 84/100 ↑ safer. Will AI replace them? Nah.

What the AIs say

We asked four AI assistants the same question: will AI replace this job in the next 10 years? One word (Yes, Partly or No), then one sentence. Our own answer, from the data: Still needs a human: 84/100 ↑ safer. Will AI replace them? Nah.

ChatGPTPartly

AI may automate some tracking, monitoring, and logistics tasks, but human hunters and wildlife professionals will still be needed for field judgment, safety, ethics, and regulation.

gpt-5.5-2026-04-23 · asked 2026-10-03
ClaudeNo

Hunting-related work relies heavily on physical presence in unpredictable natural environments, hands-on tracking skills, and contextual judgment that AI and robotics are unlikely to fully replicate within just 10 years.

claude-sonnet-5 · asked 2026-10-03
GeminiNo

While AI will improve wildlife tracking, population monitoring, and gear, the physical, unpredictable, and legally constrained nature of hunting makes fully autonomous replacement within the next decade highly improbable.

gemini-3.8-flash · asked 2026-10-03
PerplexityPartly

AI will automate scouting, tracking, and administrative tasks, but physical harvesting and field judgment will still require human workers.

sonar · asked 2026-10-03

Assistants answer from what they learned in training (Perplexity also searches the web), so they can be confidently wrong, and the same question can get a different answer tomorrow. Our score is built from task data and graded evidence. Answers collected through DataForSEO.

Cite this page

NeedsAHuman.com (2026). Will AI replace Fishing and Hunting Workers? Nah. Still needs a human: 84/100, higher is safer; release 2026-Q4. https://needsahuman.com/jobs/fishing-and-hunting-workers/ (accessed 4 October 2026).

Scores change with each , so cite the release. The data is open under : credit NeedsAHuman.com with a link. Open data · Press

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The badge updates itself with each release and links back to this page.

Sources

  • Tasks and work context: 31.0, ().
  • Jobs, pay and projections: US , and 2025–35.
  • How AI is used today: ; Microsoft Research, .
  • What AI can do: our task ratings ( r1) and the quality evidence register.
  • UK names and employment: coding index and .

How each score is built: methodology. Every figure on this page: open data. Release 2026-Q4.