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

Data architect

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
Models, lineage and the catalogue.
Estimate

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

18%52%+9.4
Pipelines, quality and the data contract.
Estimate

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

16%40%+6.4
The analyst who finds nothing and the mess.
Estimate

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

16%22%+3.5
Privacy, retention and the field you cannot keep.
Estimate

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

16%28%+4.5
The business, shadow IT and not building another lake.
Estimate

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

18%14%+2.5
That it gets used, and not letting raw data rot.
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

  • model data
  • lineage
  • data catalogue
  • data contracts
  • pipeline quality
  • retention
  • data lakes
  • privacy

Sources for this job· O*NET 15-1243.00· ESCO/ISCO 2511

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