Automation index
How much of a Audiologist’s job can AI already do?
An audiogram and a curve tweak come earlier. Fitting an aid so the person actually hears does not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Audiologist
23%
AI can already do 23% of this job.
#288 / 633
View rankingAudiologist
Where the time goes
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 |
|---|---|---|---|
Audiograms, thresholds and a first fit.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 40% | +7.2 |
Trial, mould and adapt the aid.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Explain, habituation and follow-up.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Reports for ENT and notes.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Repair, clean and prototype stock.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Children, older people and not overselling.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 23% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Audiograms, thresholds and a first fit
- Trial, mould and adapt the aid
- Explain, habituation and follow-up
- Reports for ENT and notes
- Repair, clean and prototype stock
- Children, older people and not overselling
- audiologo
- audiologist
Sources for this job· O*NET 29-1181.00· ESCO/ISCO 2266
IS WORK OVER?
Data architect
28%
#83 / 633
View rankingData architect
Where the time goes
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 |
|---|---|---|---|
Models, lineage and the catalogue.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Pipelines, quality and the data contract.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
The analyst who finds nothing and the mess.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Privacy, retention and the field you cannot keep.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The business, shadow IT and not building another lake.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
That it gets used, and not letting raw data rot.EstimateNo 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
Skills and activities
- model data
- lineage
- data catalogue
- data contracts
- pipeline quality
- retention
- data lakes
- privacy
Sources for this job· O*NET 15-1243.00· ESCO/ISCO 2511