Automation index

How much of a Air traffic controller’s job can AI already do?

Labels and alerts already help. Separating two aircraft in fog, and talking to both, is not something you hand off.

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

Task comparison

IS WORK OVER?

17%

AI can already do 17% of this job.

#598 / 643

Air traffic controller

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
Plan sequences and read traffic forecasts. Estimate No public source provides a precise figure. This is our estimate.	18%	32%	+5.8
Strips, tickets and inter-unit coordination. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
Tactical control of aircraft on frequency. Estimate No public source provides a precise figure. This is our estimate.	22%	6%	+1.3
Resolve conflicts, radio failures and weather. Estimate No public source provides a precise figure. This is our estimate.	16%	10%	+1.6
Train and supervise a controller under instruction. Estimate No public source provides a precise figure. This is our estimate.	14%	12%	+1.7
Reports, incidents and shift fatigue. Estimate No public source provides a precise figure. This is our estimate.	14%	15%	+2.1
Total	100%		17%

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

IS WORK OVER?

26%

#216 / 643

Last-mile manager

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. Estimate No public source provides a precise figure. This is our estimate.	16%	44%	+7
KPIs, first attempt and incidents. Estimate No 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. Estimate No public source provides a precise figure. This is our estimate.	18%	16%	+2.9
Peaks, rain and hiring too many or too few. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
The angry customer and not dressing delivered. Estimate No public source provides a precise figure. This is our estimate.	18%	18%	+3.2
Cover the peak, and not leaving the neighbourhood orphaned. Estimate No 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