Automation index

How much of a Hearing aid technician’s job can AI already do?

An earmould and a gain curve come earlier. Getting the patient to hear and live with it do not.

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

Task comparison

IS WORK OVER?

24%

AI can already do 24% of this job.

#296 / 683

Hearing aid technician

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
Audiometry, thresholds and the fitting. Estimate No public source provides a precise figure. This is our estimate.	16%	40%	+6.4
Take the mould, trial and the one who hates the whistle. Estimate No public source provides a precise figure. This is our estimate.	18%	18%	+3.2
Program, verify and retune the aid. Estimate No public source provides a precise figure. This is our estimate.	16%	32%	+5.1
Repair, batteries and aftercare. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
Explain, family and the stigma of the device. Estimate No public source provides a precise figure. This is our estimate.	18%	14%	+2.5
That they actually hear, and not taking the aid back. Estimate No public source provides a precise figure. This is our estimate.	16%	12%	+1.9
Total	100%		24%

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

IS WORK OVER?

27%

#206 / 683

University tutor

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
Form, the file and the one who does not come. Estimate No public source provides a precise figure. This is our estimate.	18%	48%	+8.6
Mark, the cut and the one who gives up. Estimate No public source provides a precise figure. This is our estimate.	16%	40%	+6.4
Grant, the paper and not letting it lapse. Estimate No public source provides a precise figure. This is our estimate.	16%	22%	+3.5
Health, the referral and not playing clinician. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
The dean, the dropout figure and not dressing it. Estimate No public source provides a precise figure. This is our estimate.	18%	14%	+2.5
That they ask for help, and not dropping out. 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