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

Route planner

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
Optimise, windows and capacity.
Estimate

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

18%52%+9.4
Restrictions, tolls and the right vehicle.
Estimate

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

16%40%+6.4
The salesperson who promises and the plan that will not.
Estimate

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

16%22%+3.5
Recalc, incidents and the next day.
Estimate

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

16%28%+4.5
The warehouse, the cut-off and not leaving the last one.
Estimate

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

18%14%+2.5
That it fits, and not blowing the hours.
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

  • optimise routes
  • delivery windows
  • tolls
  • vehicle capacity
  • recalc
  • traffic restrictions
  • warehouse cut-off
  • driving hours

Sources for this job· O*NET 13-1081.00· ESCO/ISCO 4323

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