IS WORK OVER?

Automation index

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

Triage and a protocol come earlier. Deciding in five minutes and telling the family do not.

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

Task comparison

Emergency physician

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
Read vitals, ECG and shock protocols.
Estimate

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

16%32%+5.1
Assess, stabilise and prioritise beds.
Estimate

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

22%10%+2.2
Procedures: line, suture, CPR.
Estimate

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

16%18%+2.9
Brief family and negotiate doubtful discharges.
Estimate

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

16%22%+3.5
Notes, consults and ward admissions.
Estimate

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

16%28%+4.5
Shift, team and not leaving anyone in the corridor.
Estimate

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

14%12%+1.7
Total100%20%

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

Skills and activities

  • care for patients
  • diagnose
  • nursing care
  • clinical notes
  • Read vitals, ECG and shock protocols
  • Assess, stabilise and prioritise beds
  • Procedures: line, suture, CPR
  • Notes, consults and ward admissions
  • medico de urgencias
  • urgentologo

Sources for this job· O*NET 29-1214.00· 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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