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.

#281 / 633

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?

15%

#620 / 633

Bus driver

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
Run sheet, logs and clocking. Estimate No public source provides a precise figure. This is our estimate.	16%	32%	+5.1
Drive the route or the charter. Estimate No public source provides a precise figure. This is our estimate.	22%	8%	+1.8
Stops, accessibility and fare or validation. Estimate No public source provides a precise figure. This is our estimate.	18%	10%	+1.8
Incidents, diversions and passenger care. Estimate No public source provides a precise figure. This is our estimate.	16%	12%	+1.9
Pre-trip check and defect reports. Estimate No public source provides a precise figure. This is our estimate.	14%	18%	+2.5
Shifts, fatigue and driving rules. Estimate No public source provides a precise figure. This is our estimate.	14%	15%	+2.1
Total	100%		15%

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