Automation index
How much of a Energy engineer’s job can AI already do?
A load curve comes earlier. Cutting the bill without leaving the process in the dark do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Energy engineer
27%
AI can already do 27% of this job.
#160 / 623
View rankingEnergy 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 |
|---|---|---|---|
Energy audit, curves and the saving potential.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
Contracts, tariffs and the power market.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 36% | +5.8 |
Plant, meters and what the meter misses.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Efficiency projects and the real payback.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The board, the CAPEX and the no to the project.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Save for real, and not selling green smoke.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
- energy audit
- load curves
- power tariffs
- energy efficiency
- CAPEX payback
- plant metering
- power market
- real savings
Sources for this job· O*NET 17-2199.00· ESCO/ISCO 2149
IS WORK OVER?
Climatologist
27%
#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