IS WORK OVER?

Automation index

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

A checklist and a count come earlier. Scrubbing and not missing a swab do not.

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

Task comparison

Operating room 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
Set the table, checklist and the patient card.
Estimate

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

16%36%+5.8
Scrub, anticipate and not break the field.
Estimate

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

22%8%+1.8
Count swabs, needles and the record.
Estimate

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

16%22%+3.5
Circulate, stocks and the turnaround.
Estimate

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

16%28%+4.5
Emergency, the bleeder and the table change.
Estimate

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

16%18%+2.9
Nothing left inside and signing the count.
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

  • scrub
  • surgical checklist
  • swab count
  • set the table
  • circulate
  • sterile field
  • theatre
  • anticipate the surgeon

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

Station master

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
Graph, orders and the station log.
Estimate

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

16%40%+6.4
Platforms, the crossing and the late train.
Estimate

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

18%14%+2.5
Staff, shifts and the ticket-office gap.
Estimate

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

16%32%+5.1
Incident, passengers and the PA.
Estimate

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

16%22%+3.5
Works, closures and leaving nobody on the platform.
Estimate

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

18%18%+3.2
That they do not meet, and signing the graph.
Estimate

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

16%12%+1.9
Total100%23%

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

Skills and activities

  • train graph
  • orders
  • platforms
  • ticket office
  • PA
  • line crossings
  • station shifts
  • station logs

Sources for this job· O*NET 53-4031.00· ESCO/ISCO 4323

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