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?

28%

#109 / 633

BIM modeller

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
Model, families and clash detection. Estimate No public source provides a precise figure. This is our estimate.	18%	52%	+9.4
IFC, BEP and trade coordination. Estimate No public source provides a precise figure. This is our estimate.	16%	40%	+6.4
Site, the one who will not open the model, and the meeting. Estimate No public source provides a precise figure. This is our estimate.	16%	22%	+3.5
Quantities, parameters and the 4D nobody uses. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
The last-minute change and not breaking the federated model. Estimate No public source provides a precise figure. This is our estimate.	18%	14%	+2.5
That it can be built, and not over-modelling. Estimate No public source provides a precise figure. This is our estimate.	16%	12%	+1.9
Total	100%		28%

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