Automation index

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

Finding a flight and a hotel come earlier. Building a trip that holds, and answering when it does not, do not.

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

Task comparison

IS WORK OVER?

29%

AI can already do 29% of this job.

#55 / 623

Travel agent

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
Search flights, hotels, trains and packages. Estimate No public source provides a precise figure. This is our estimate.	18%	52%	+9.4
Quote, compare and issue bookings. Estimate No public source provides a precise figure. This is our estimate.	16%	40%	+6.4
Serve the client: taste, visas and fears. Estimate No public source provides a precise figure. This is our estimate.	18%	18%	+3.2
Changes, cancellations and incidents on the ground. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
Groups, corporates and tailor-made trips. Estimate No public source provides a precise figure. This is our estimate.	16%	22%	+3.5
Suppliers, margins and liability for the booking. Estimate No public source provides a precise figure. This is our estimate.	16%	14%	+2.2
Total	100%		29%

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

IS WORK OVER?

26%

#211 / 623

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