Automation index

How much of a Switchboard operator’s job can AI already do?

A switchboard comes earlier. Putting the call through without hanging up on the one who waits do not.

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

Task comparison

IS WORK OVER?

27%

AI can already do 27% of this job.

#187 / 633

Switchboard operator

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
Board, destinations and the shift. Estimate No public source provides a precise figure. This is our estimate.	18%	48%	+8.6
The call, the one who is out and the message. Estimate No public source provides a precise figure. This is our estimate.	16%	40%	+6.4
Emergencies, the anger and not losing it. Estimate No public source provides a precise figure. This is our estimate.	16%	22%	+3.5
Directory, changes and not putting through wrong. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
The peak, the queues and not hanging up. Estimate No public source provides a precise figure. This is our estimate.	18%	14%	+2.5
Put it through, and not hanging up on the one who waits. Estimate No public source provides a precise figure. This is our estimate.	16%	12%	+1.9
Total	100%		27%

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