IS WORK OVER?

Automation index

How much of a Home-automation installer’s job can AI already do?

A scene comes earlier. The house obeying without going dark do not.

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

Task comparison

Home-automation installer

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
Diagram, buses and scene programming.
Estimate

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

16%40%+6.4
Wire, sensors and the switch that does not answer.
Estimate

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

18%14%+2.5
Integrate lights, climate and the client app.
Estimate

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

16%32%+5.1
Train, guest mode and the one who breaks it.
Estimate

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

16%22%+3.5
The lived-in house and not leaving it dark.
Estimate

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

18%18%+3.2
That it obeys, and not needing the cloud for a switch.
Estimate

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

16%12%+1.9
Total100%23%

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

Skills and activities

  • program scenes
  • home buses
  • integrate climate
  • sensors
  • home app
  • switches
  • guest mode
  • wire KNX

Sources for this job· O*NET 47-2111.00· ESCO/ISCO 7411

Strength and conditioning coach

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
Load, GPS and the microcycle.
Estimate

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

16%40%+6.4
Gym, the pattern and the one who cheats.
Estimate

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

18%14%+2.5
Rehab, the injured and not rushing the return.
Estimate

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

16%28%+4.5
Report, the manager and the fight over minutes.
Estimate

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

16%22%+3.5
The peak, pre-season and not grinding them.
Estimate

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

18%18%+3.2
Ready, and not broken.
Estimate

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

16%12%+1.9
Total100%22%

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

Skills and activities

  • load
  • training GPS
  • microcycles
  • rehab
  • movement pattern
  • pre-season
  • reports to the manager
  • the gym

Sources for this job· O*NET 29-9091.00· ESCO/ISCO 3423

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