IS WORK OVER?

Automation index

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

Guided set-up comes earlier. Immobilising every day and not missing the field do not.

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

Task comparison

Radiation therapist

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
Plan, IGRT and the day’s set-up.
Estimate

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

16%40%+6.4
Immobilise, tattoo and treat fraction by fraction.
Estimate

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

22%12%+2.6
Check images, shifts and call the physician.
Estimate

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

16%28%+4.5
Side effects, the patient who cries and the wait.
Estimate

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

16%22%+3.5
Machine QA and alarms.
Estimate

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

16%32%+5.1
Today’s dose and not irradiating the wrong thing.
Estimate

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

14%14%+2
Total100%24%

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

Skills and activities

  • set up for RT
  • IGRT
  • immobilise patients
  • deliver fractions
  • linac QA
  • reference tattoos
  • shifts
  • radiotherapy

Sources for this job· O*NET 29-1124.00· ESCO/ISCO 3211

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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