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
IS WORK OVER?
Airport ramp agent
21%
AI can already do 21% of this job.
#413 / 643
View rankingAirport 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.
| Task | Share | AI | Points |
|---|---|---|---|
Load plan, LIR and hold allocation.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Load, unload, pushback and ramp assistance.EstimateNo public source provides a precise figure. This is our estimate. | 22% | 8% | +1.8 |
Bags, ULDs and special cargo.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Coordinate with crew, ops and fuel.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Times, delays and ramp safety.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Trim, papers and liability for the load.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 12% | +1.7 |
| Total | 100% | 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
IS WORK OVER?
Last-mile manager
26%
#216 / 643
View rankingLast-mile manager
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.
| Task | Share | AI | Points |
|---|---|---|---|
Zones, capacity and route cuts.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 44% | +7 |
KPIs, first attempt and incidents.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 36% | +5.8 |
The courier, the lobby and the one who will not open.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 16% | +2.9 |
Peaks, rain and hiring too many or too few.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The angry customer and not dressing delivered.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Cover the peak, and not leaving the neighbourhood orphaned.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 26% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- delivery zones
- first attempt
- delivery KPIs
- last-mile peaks
- lobbies
- delivery incidents
- courier capacity
- cut routes
Sources for this job· O*NET 11-3071.00· ESCO/ISCO 1324