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?

27%

AI can already do 27% of this job.

#160 / 623

Energy engineer

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. Estimate No public source provides a precise figure. This is our estimate.	18%	48%	+8.6
Contracts, tariffs and the power market. Estimate No public source provides a precise figure. This is our estimate.	16%	36%	+5.8
Plant, meters and what the meter misses. Estimate No public source provides a precise figure. This is our estimate.	16%	22%	+3.5
Efficiency projects and the real payback. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
The board, the CAPEX and the no to the project. Estimate No public source provides a precise figure. This is our estimate.	18%	14%	+2.5
Save for real, and not selling green smoke. Estimate No 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

IS WORK OVER?

31%

#33 / 623

Information specialist

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
Classify, index and describe holdings. Estimate No public source provides a precise figure. This is our estimate.	18%	48%	+8.6
Thesauri, metadata and the internal search. Estimate No public source provides a precise figure. This is our estimate.	16%	52%	+8.3
Answer queries and retrieve what nobody can find. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
Records policy, retention and destruction. Estimate No public source provides a precise figure. This is our estimate.	18%	22%	+4
Train people who file badly and people who do not file. Estimate No public source provides a precise figure. This is our estimate.	16%	18%	+2.9
The organisation’s memory, and not losing it. Estimate No public source provides a precise figure. This is our estimate.	16%	14%	+2.2
Total	100%		30%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low