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

Cartographer

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
Sources, OSM, satellite and generalisation.
Estimate

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

18%52%+9.4
Symbology, type and visual hierarchy.
Estimate

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

16%48%+7.7
Projections, scales and getting the heights right.
Estimate

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

16%28%+4.5
Review with the client, the field and the lie in the data.
Estimate

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

18%18%+3.2
Print maps, web maps and updates.
Estimate

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

16%22%+3.5
Credit, metadata and owning the map.
Estimate

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

16%14%+2.2
Total100%31%

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

Skills and activities

  • make maps
  • generalise cartography
  • symbology
  • choose projection
  • visual hierarchy
  • update OSM
  • web maps
  • maps that do not lie

Sources for this job· O*NET 17-1021.00· ESCO/ISCO 2165

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