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.

#379 / 643

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?

31%

#33 / 643

Information specialist

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
Classify, index and describe holdings. Estimate No public source provides a precise figure. This is our estimate.	18%	48%	+8.6
Thesauri, metadata and the internal search. Estimate No public source provides a precise figure. This is our estimate.	16%	52%	+8.3
Answer queries and retrieve what nobody can find. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
Records policy, retention and destruction. Estimate No public source provides a precise figure. This is our estimate.	18%	22%	+4
Train people who file badly and people who do not file. Estimate No public source provides a precise figure. This is our estimate.	16%	18%	+2.9
The organisation’s memory, and not losing it. Estimate No public source provides a precise figure. This is our estimate.	16%	14%	+2.2
Total	100%		30%

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