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Managers · code 1312

Aquaculture and fisheries production managers

AI can run the budget and forecast prices. It can't tell a sick fish from a healthy one.

AI barely touches eight of the thirteen tasks, like directing the spawning, rearing and moving of fish. Budgets, records and managing workers are mostly out of its reach too.

What they actually do (and what else they get called)

Aquaculture and fisheries production managers plan, direct and coordinate production in large-scale aquaculture and fishery operations to catch and harvest fish and shellfish, and to grow fish, shellfish or other forms of aquatic life as cash crops or for release into freshwater or saltwater. Tasks include - (a) monitoring aquaculture and fishery market activity and planning production and fishing activities to meet contract requirements and market demand; (b) establishing and managing budgets, monitoring production output and costs, recording information such as fisheries management practices, and preparing financial and operational reports; (c) conferring with buyers to arrange for the sale of produce and catches; (d) contracting with fishing skippers or owners of vessels and aquaculture farms for fishing and aquaculture operations, or for management of production; (e) conducting and organizing aquaculture or fishery stock examinations in order to identify diseases or parasites; (f) devising and coordinating activities to improve fish hatching and growth rates, and to prevent disease in hatcheries; (g) monitoring environments to maintain or improve conditions for aquatic life; (h) directing and monitoring trapping and spawning of fish, egg incubation and fry rearing, applying knowledge of management and fish culturing techniques; (i) coordinating the selection and maintenance of brood stock; (j) directing and monitoring the transfer of mature fish to lakes, ponds, streams or commercial tanks; (k) purchasing machinery, equipment and supplies such as vessels and nets; (l) organizing operations such as maintenance of ships, boats and equipment; (m) overseeing the selection, training and performance of aquaculture or fishery workers and contractors. Examples of the occupations classified here: - Aquaculture production manager - Fishing operations manager - Shore captain (fishing) - Trawler manager Some related occupations classified elsewhere: - Fish farmer - 6221 - Fish hatchery manager - 6221 - Oyster farmer - 6221 - Seafood farmer - 6221 - Fishing vessel skipper (coastal waters) - 6222 - Fishing master (deep sea) - 6223

  • aquaculture harvesting manager
  • aquaculture husbandry manager
  • aquaculture production manager

Job titles from the EU's ESCO list. Search for any of them on the jobs page and you'll end up here.

78 / 100

Mostly holds up against AI

AI can take a few chores off your plate, but most of the day is still yours.

Not the odds you keep your job. It's how much of the everyday work still needs a person, out of 100.

← Robot's turf Human's turf →

The ILO's official verdict: Not Exposed

167 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 13 tasks for how much of it AI could do. They average 22 out of 100, so it holds up at 100 − 22 = 78.

That's the whole sum. No black box, no secret sauce: you can check it against the ILO's study. ILO group “Not Exposed”: None of this job's tasks scored high enough to count.

from the source Working Paper 140, Generative AI and Jobs 2025 index data 0.8-observed-use

Pinch of salt: this number is probably too rosy

It only asks what AI software could do, and this job is 62 out of 100 hands-on. A chatbot can't do that part. A robot might, one day, and nobody measures how close that is.

Man v Bot · compare

Who holds up better?

Aquaculture and fisheries production managers 78

v

Go on, try your partner's job. Or your sibling's. We won't tell.

Man v Bot

Where the bot helps, and where the human wins

Bot

What AI takes

The routine stuff. You may not miss it.

  • Budgets, costs and production records.
  • Market planning and sales.
  • Water quality monitoring with sensors.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Managing fish health and disease.
  • Leading crews and contractors.
  • Decisions when conditions change.

Both

What's arriving

New work that only exists because the AI does.

  • Automated feeding and monitoring.
  • Sustainability certification.
  • Seaweed and shellfish farming.

Written by a human, from the ILO's task ratings below. Yes, we see the irony. Read it as one person's take.

Meet your two rivals

They're not the same machine. AI software can only reach the parts of a job done on a screen or in words. A chatbot can't climb a ladder. A robot might, one day, if it doesn't fall off.

The AI

Lives in a screen. Never had to fix a boiler.

Threat level: Medium

41 could do without you

It could take over some of the work, and help with more. It could help with 66 of 100.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Higher

62 how hands-on

Most of this job needs hands, a body or turning up. That's robot territory, and nobody measures how far robots have got well enough to give you a number. We won't make one up.

So could a robot do the physical part?

Less fine handwork and fewer cramped spaces than a typical hands-on job. That clears one hurdle for machines. It doesn't mean machines are doing this work yet.

Robots hate fiddly work in awkward spaces. On that measure, this job scores 34 out of 100. The higher it is, the longer the robot waits.

62 How
hands-on
34 How fiddly
and cramped

Kind of hands-on work Hands-on, less fiddly work

The small print

They aren't a robot score, and nothing on this page is. Nobody measures how far robots have got well enough to put a number on it. These are the closest thing we have: how hands-on the job is, and how much fiddly, cramped work it takes, which is what Frey and Osborne found hardest for machines.

From O*NET, matched to one US job .

finger skill 35.7 · hand skill 35.7 · cramped spaces 31.3 · averaged · rule: hands-on 50+ · fiddly under 39.4

estimated O*NET 31.0 BLS occupational crosswalk chain ISCO-08 to 2010 SOC (Aug 2012, rev. Jun 2015); 2010 to 2018 SOC (Nov 2017); O*NET-SOC 2019 taxonomy data 0.8-observed-use measures chosen by Frey & Osborne (2017) · the grouping is a sorting, not a measurement

The job, task by task

Every job is really a bundle of tasks. Here's this one unpacked, with how much of each AI could do, out of 100. The score is the average, and averages can hide a lot.

AI's favourite task here scores 41, against an average of 22. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 41

    Establishing and managing budgets, monitoring production output and costs, recording information such as fisheries management practices, and preparing financial and operational reports

    Low
  2. 30

    Overseeing the selection, training and performance of aquaculture or fishery workers and contractors.

    Low
  3. 28

    Monitoring aquaculture and fishery market activity and planning production and fishing activities to meet contract requirements and market demand

    Low
  4. 28

    Conferring with buyers to arrange for the sale of produce and catches

    Low
  5. 27

    Coordinating the selection and maintenance of brood stock

    Low
  6. 22

    Contracting with fishing skippers or owners of vessels and aquaculture farms for fishing and aquaculture operations, or for management of production

    Very Low
  7. 21

    Devising and coordinating activities to improve fish hatching and growth rates, and to prevent disease in hatcheries

    Very Low
  8. 18

    Purchasing machinery, equipment, and supplies such as vessels and nets

    Very Low
  9. 15

    Organizing operations such as maintenance of ships, boats and equipment

    Very Low
  10. 15

    Conducting and organizing aquaculture or fishery stock examinations in order to identify diseases or parasites

    Very Low
  11. 14

    Monitoring environments to maintain or improve conditions for aquatic life

    Very Low
  12. 14

    Directing and monitoring trapping and spawning of fish, egg incubation, and fry rearing, applying knowledge of management and fish culturing techniques

    Very Low
  13. 14

    Directing and monitoring the transfer of mature fish to lakes, ponds, streams, or commercial tanks

    Very Low

13 tasks · the High to Very Low labels are the ILO's

from the source Working Paper 140, Generative AI and Jobs 2025 index data 0.8-observed-use

Sidekick or replacement?

A tool that makes you faster is a very different thing from one that does the task while you watch. Jobs and Skills Australia measured the two separately, which is handy.

AI helps you
66
AI does it for you
41

Sidekick wins, by 25 points.

How good a match is this?

One Australian job matches this one closely, so this is about as reliable as it gets here.

estimated Our Gen AI Transition (Gen AI Capacity Study) September 2025 detailed data release data 0.8-observed-use matched to Australian jobs 1211

So, should aquaculture and fisheries managers be worried?

Short answer: not much. Some of the chores will change, and good riddance.

Parts of the management side are changing. Budgets, staffing, market planning, sales and brood stock choices are the most exposed tasks, all Low; examining stock and running hatcheries rate Very Low. Software and sensors will help plan; fish farming stays hands-on.

Worth remembering: we score tasks, not jobs. When AI takes on a task, the job usually reshuffles around it rather than vanishing.

Where this job could lead

None of the new jobs we've written up start from here yet. Could be you're the first. See the jobs AI is creating →

How are the neighbours doing?

There are 30 jobs in the “Managers” family, averaging 63. This one is above the family average.

Pit this against any other job →