IS WORK OVER?

Automation index

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

A vitals log comes earlier. Catching the change and calling in time do not.

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

Task comparison

ICU nurse

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
Charts, pumps and the bed plan.
Estimate

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

16%36%+5.8
Lines, ventilator and the patient who crashes.
Estimate

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

22%8%+1.8
Hygiene, turning and preventing sores.
Estimate

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

16%22%+3.5
Family at the bed and the news.
Estimate

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

16%28%+4.5
On-call, admissions and handover.
Estimate

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

16%18%+2.9
Catch the change and owning the bed.
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

  • ICU care
  • run the ventilator
  • central lines
  • chart vitals
  • prevent sores
  • ICU handover
  • infusion pumps
  • call the intensivist

Sources for this job· O*NET 29-1141.00· ESCO/ISCO 2221

Last-mile manager

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
Zones, capacity and route cuts.
Estimate

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

16%44%+7
KPIs, first attempt and incidents.
Estimate

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

16%36%+5.8
The courier, the lobby and the one who will not open.
Estimate

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

18%16%+2.9
Peaks, rain and hiring too many or too few.
Estimate

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

16%28%+4.5
The angry customer and not dressing delivered.
Estimate

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

18%18%+3.2
Cover the peak, and not leaving the neighbourhood orphaned.
Estimate

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

16%14%+2.2
Total100%26%

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

Skills and activities

  • delivery zones
  • first attempt
  • delivery KPIs
  • last-mile peaks
  • lobbies
  • delivery incidents
  • courier capacity
  • cut routes

Sources for this job· O*NET 11-3071.00· ESCO/ISCO 1324

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