Automation index

How much of a Last-mile manager’s job can AI already do?

A zone map comes earlier. Hitting the peak without leaving the neighbourhood without a courier do not.

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

Task comparison

IS WORK OVER?

26%

AI can already do 26% of this job.

#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

IS WORK OVER?

25%

#230 / 623

Biomedical engineer

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
Design, validate and document clinical devices and software. Estimate No public source provides a precise figure. This is our estimate.	18%	48%	+8.6
Tests, MDR and risk. Estimate No public source provides a precise figure. This is our estimate.	16%	32%	+5.1
Hospital, clinicians and maintenance. Estimate No public source provides a precise figure. This is our estimate.	16%	22%	+3.5
Vendors, quality and traceability. Estimate No public source provides a precise figure. This is our estimate.	16%	18%	+2.9
User training and post-market watch. Estimate No public source provides a precise figure. This is our estimate.	18%	16%	+2.9
Not putting a half-built prototype in theatre. Estimate No public source provides a precise figure. This is our estimate.	16%	14%	+2.2
Total	100%		25%

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