IS WORK OVER?

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

Energy 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.

TaskShareAIPoints
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
Total100%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

Logistics analyst

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.

TaskShareAIPoints
Costs, OTIF and the dashboard.
Estimate

No public source provides a precise figure. This is our estimate.

18%52%+9.4
Simulate network, warehouses and the what-if.
Estimate

No public source provides a precise figure. This is our estimate.

16%40%+6.4
Ops, dirty data and going down to the dock.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Report, the board and the cut that hurts.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
The haulier, the contract and not breaking the service.
Estimate

No public source provides a precise figure. This is our estimate.

18%14%+2.5
A real saving, and not dressing OTIF.
Estimate

No public source provides a precise figure. This is our estimate.

16%12%+1.9
Total100%28%

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

Skills and activities

  • logistics costs
  • OTIF
  • simulate network
  • what-if
  • dirty data
  • haulage contracts
  • dashboards
  • network cuts

Sources for this job· O*NET 13-1081.00· ESCO/ISCO 2421

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