IS WORK OVER?

Automation index

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

A clinic diary comes earlier. The patient going in and the record being there do not.

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

Task comparison

Medical secretary

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
Diary, appointments and the DNA.
Estimate

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

18%48%+8.6
Record, the report and the missing one.
Estimate

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

16%40%+6.4
Phone, results and not giving them wrong.
Estimate

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

16%22%+3.5
The doctor, the delay and not wrecking the waiting room.
Estimate

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

16%28%+4.5
Confidentiality and not talking in the corridor.
Estimate

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

18%14%+2.5
The patient goes in, and the record is there.
Estimate

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

16%12%+1.9
Total100%27%

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

Skills and activities

  • clinic diary
  • records
  • results
  • confidentiality
  • waiting room
  • medical appointments
  • reports
  • DNAs

Sources for this job· O*NET 43-6013.00· ESCO/ISCO 3344

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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