Automation index

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

A crime map comes earlier. Understanding why it happens there, and what to do with the repeat offender, 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.

#57 / 623

Criminologist

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
Data, maps and the victimisation report. Estimate No public source provides a precise figure. This is our estimate.	18%	48%	+8.6
Profiles, reoffending and programme evaluation. Estimate No public source provides a precise figure. This is our estimate.	16%	40%	+6.4
Field, interviews and what the spreadsheet misses. Estimate No public source provides a precise figure. This is our estimate.	18%	18%	+3.2
Police, judges and the measure under debate. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
Prevention, the neighbourhood and the programme that does not fit. Estimate No public source provides a precise figure. This is our estimate.	16%	22%	+3.5
The opinion, and not selling magic recipes. Estimate No public source provides a precise figure. This is our estimate.	16%	14%	+2.2
Total	100%		28%

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