IS WORK OVER?

Automation index

How much of a Airport ramp agent’s job can AI already do?

A load plan comes earlier. Pushing the aircraft, the bags and not getting the trim wrong do not.

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

Task comparison

Airport ramp agent

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 plan, LIR and hold allocation.
Estimate

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

16%40%+6.4
Load, unload, pushback and ramp assistance.
Estimate

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

22%8%+1.8
Bags, ULDs and special cargo.
Estimate

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

16%22%+3.5
Coordinate with crew, ops and fuel.
Estimate

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

16%28%+4.5
Times, delays and ramp safety.
Estimate

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

16%18%+2.9
Trim, papers and liability for the load.
Estimate

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

14%12%+1.7
Total100%21%

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

Skills and activities

  • load aircraft
  • do pushback
  • allocate holds
  • move bags
  • load planning
  • ramp assistance
  • handle ULDs
  • ramp safety

Sources for this job· O*NET 53-6051.00· ESCO/ISCO 9333

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

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