Automation index
How much of a Climatologist’s job can AI already do?
A series comes earlier. Attributing the change without selling the easy headline do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Climatologist
27%
AI can already do 27% of this job.
#140 / 623
View rankingClimatologist
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 |
|---|---|---|---|
Series, homogenise and the gap.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
Models, scenarios and the uncertainty.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Report, the headline and not selling the easy one.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Field, the station and the one that moves.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The politician, the figure and not staying quiet.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Attribute, and not selling the headline.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 27% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- climate series
- homogenise
- scenarios
- uncertainty
- headlines
- stations
- climate reports
- attribution
Sources for this job· O*NET 19-2021.00· ESCO/ISCO 2112
IS WORK OVER?
Prompt engineer
34%
#21 / 623
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