Automation index

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

A score comes earlier. Sounding together without hating the instrument do not.

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

Task comparison

IS WORK OVER?

22%

AI can already do 22% of this job.

#370 / 633

Music teacher

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
Score, tuning and the term plan. Estimate No public source provides a precise figure. This is our estimate.	16%	40%	+6.4
Class, the one out of tune and the one who does not practise. Estimate No public source provides a precise figure. This is our estimate.	18%	14%	+2.5
Rehearsal, the concert and the one who is ill. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
Assess, auditions and not humiliating. Estimate No public source provides a precise figure. This is our estimate.	16%	22%	+3.5
Families, the instrument and the one that will not fit at home. Estimate No public source provides a precise figure. This is our estimate.	18%	18%	+3.2
Sound together, and not hating the instrument. Estimate No public source provides a precise figure. This is our estimate.	16%	12%	+1.9
Total	100%		22%

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