IS WORK OVER?

Automation index

How much of a Automation engineer’s job can AI already do?

A PLC and a SCADA come earlier. Leaving the plant in auto without it tripping do not.

This percentage does not predict how many people will lose their jobs.

Task comparison

Automation 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
PLC, SCADA and the interlock.
Estimate

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

18%48%+8.6
Panel, loops and the lying sensor.
Estimate

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

16%22%+3.5
FAT, SAT and commissioning.
Estimate

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

16%36%+5.8
Recipes, batches and the product change.
Estimate

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

16%28%+4.5
The shift, the alarm and not bypassing the interlock.
Estimate

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

18%14%+2.5
That it does not trip, and documenting the program.
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

  • program PLCs
  • SCADA
  • interlocks
  • control loops
  • FAT SAT
  • commissioning
  • plant alarms
  • automation panels

Sources for this job· O*NET 17-3024.00· ESCO/ISCO 2149

Last-mile manager

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
Zones, capacity and route cuts.
Estimate

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

16%44%+7
KPIs, first attempt and incidents.
Estimate

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

16%36%+5.8
The courier, the lobby and the one who will not open.
Estimate

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

18%16%+2.9
Peaks, rain and hiring too many or too few.
Estimate

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

16%28%+4.5
The angry customer and not dressing delivered.
Estimate

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

18%18%+3.2
Cover the peak, and not leaving the neighbourhood orphaned.
Estimate

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

16%14%+2.2
Total100%26%

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

Skills and activities

  • delivery zones
  • first attempt
  • delivery KPIs
  • last-mile peaks
  • lobbies
  • delivery incidents
  • courier capacity
  • cut routes

Sources for this job· O*NET 11-3071.00· ESCO/ISCO 1324

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