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?
Prompt engineer
34%
#21 / 633
View rankingPrompt engineer
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 |
|---|---|---|---|
Design prompts, tools and chains.EstimateNo public source provides a precise figure. This is our estimate. | 24% | 58% | +13.9 |
Evals, datasets and regressions.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Integrate with product and safety limits.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Talk to the business about a good output.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Watch hallucinations, bias and cost.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 20% | +2.8 |
Decide what the model gets, and what it does not.EstimateNo public source provides a precise figure. This is our estimate. | 12% | 16% | +1.9 |
| Total | 100% | 34% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Design prompts, tools and chains
- Evals, datasets and regressions
- Integrate with product and safety limits
- Talk to the business about a good output
- Watch hallucinations, bias and cost
- prompt engineer
- ingeniero de prompts
- llm engineer
Sources for this job· O*NET 15-1252.00· ESCO/ISCO 2512