Automation index
How much of a Aquaculturist’s job can AI already do?
An oxygen reading and a ration come earlier. The batch not dying in the night do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Aquaculturist
22%
AI can already do 22% of this job.
#317 / 633
View rankingAquaculturist
Where the time goes
Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.
The time saving for each task is estimated separately.
| Task | Share | AI | Points |
|---|---|---|---|
Oxygen, ration and the mortality log.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Cage, net and the escape.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 12% | +2.2 |
Water quality, exchange and the bloom.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Vaccines, the vet and the batch that turns.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
The storm, the swell and not losing the cage.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Not dying in the night, and not pushing density.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 22% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- cage oxygen
- fish ration
- nets
- water quality
- aquaculture mortality
- batch vaccines
- swell
- stocking density
Sources for this job· O*NET 45-1011.00· ESCO/ISCO 6221
IS WORK OVER?
Prompt engineer
34%
#21 / 633
View rankingPrompt engineer
Where the time goes
Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.
The time saving for each task is estimated separately.
| Task | Share | AI | Points |
|---|---|---|---|
Design prompts, tools and chains.EstimateNo public source provides a precise figure. This is our estimate. | 24% | 58% | +13.9 |
Evals, datasets and regressions.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Integrate with product and safety limits.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Talk to the business about a good output.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Watch hallucinations, bias and cost.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 20% | +2.8 |
Decide what the model gets, and what it does not.EstimateNo public source provides a precise figure. This is our estimate. | 12% | 16% | +1.9 |
| Total | 100% | 34% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Design prompts, tools and chains
- Evals, datasets and regressions
- Integrate with product and safety limits
- Talk to the business about a good output
- Watch hallucinations, bias and cost
- prompt engineer
- ingeniero de prompts
- llm engineer
Sources for this job· O*NET 15-1252.00· ESCO/ISCO 2512