Automation index

How much of a Parking attendant’s job can AI already do?

A barrier comes earlier. Running the car park without wrecking the person who lost the ticket do not.

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

Task comparison

IS WORK OVER?

24%

AI can already do 24% of this job.

#260 / 633

Parking attendant

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
Barriers, tickets and the count. Estimate No public source provides a precise figure. This is our estimate.	16%	40%	+6.4
The one who cannot find the car and the one who will not pay. Estimate No public source provides a precise figure. This is our estimate.	18%	14%	+2.5
Incidents, the down barrier and the jam. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
Shift, cash and cashing up. Estimate No public source provides a precise figure. This is our estimate.	16%	32%	+5.1
The event, the full house and not blocking the street. Estimate No public source provides a precise figure. This is our estimate.	18%	18%	+3.2
Run the car park, and not wrecking the lost-ticket person. Estimate No public source provides a precise figure. This is our estimate.	16%	12%	+1.9
Total	100%		24%

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

IS WORK OVER?

26%

#211 / 633

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