IS WORK OVER?

Automation index

How much of a Internist’s job can AI already do?

A differential and a first plan come earlier. Seeing the whole complex patient does not.

This percentage does not predict how many people will lose their jobs.

Task comparison

Internist

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
Cross labs, imaging and a differential.
Estimate

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

18%48%+8.6
Ward round, examination and decisions.
Estimate

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

18%14%+2.5
Explain to family and ceilings of care.
Estimate

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

16%22%+3.5
Discharge reports, consults and boards.
Estimate

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

16%28%+4.5
Medical on-call and difficult patients.
Estimate

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

16%18%+2.9
Team, residents and not fragmenting the patient.
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

  • care for patients
  • diagnose
  • nursing care
  • clinical notes
  • Cross labs, imaging and a differential
  • Ward round, examination and decisions
  • Explain to family and ceilings of care
  • Discharge reports, consults and boards
  • Medical on-call and difficult patients
  • internista

Sources for this job· O*NET 29-1216.00· ESCO/ISCO 2212

Data 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.

TaskShareAIPoints
Models, lineage and the catalogue.
Estimate

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

18%52%+9.4
Pipelines, quality and the data contract.
Estimate

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

16%40%+6.4
The analyst who finds nothing and the mess.
Estimate

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

16%22%+3.5
Privacy, retention and the field you cannot keep.
Estimate

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

16%28%+4.5
The business, shadow IT and not building another lake.
Estimate

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

18%14%+2.5
That it gets used, and not letting raw data rot.
Estimate

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

16%12%+1.9
Total100%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

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