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?

24%

#257 / 633

Agile coach

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
Boards, metrics and the cadence design. Estimate No public source provides a precise figure. This is our estimate.	16%	40%	+6.4
The real retro and the elephant in the room. Estimate No public source provides a precise figure. This is our estimate.	18%	14%	+2.5
Train, unblock and the manager who will not let go. Estimate No public source provides a precise figure. This is our estimate.	16%	32%	+5.1
Scale, dependencies and fake agile. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
Conflict, power and not selling extra frameworks. Estimate No public source provides a precise figure. This is our estimate.	18%	18%	+3.2
That they stop faking it, and not inflating velocity. Estimate No public source provides a precise figure. This is our estimate.	16%	14%	+2.2
Total	100%		24%

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