IS WORK OVER?

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

Audiologist

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.

TaskShareAIPoints
Audiograms, thresholds and a first fit.
Estimate

No public source provides a precise figure. This is our estimate.

18%40%+7.2
Trial, mould and adapt the aid.
Estimate

No public source provides a precise figure. This is our estimate.

18%14%+2.5
Explain, habituation and follow-up.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Reports for ENT and notes.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
Repair, clean and prototype stock.
Estimate

No public source provides a precise figure. This is our estimate.

16%18%+2.9
Children, older people and not overselling.
Estimate

No public source provides a precise figure. This is our estimate.

16%14%+2.2
Total100%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

Agile coach

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.

TaskShareAIPoints
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
Total100%24%

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

Skills and activities

  • retros
  • agile cadence
  • unblock teams
  • flow metrics
  • fake agile
  • agile training
  • dependencies
  • velocity

Sources for this job· O*NET 13-1111.00· ESCO/ISCO 2421

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