Automation index

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

Assisted contouring comes earlier. Setting the field and not burning healthy tissue do not.

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

Task comparison

IS WORK OVER?

23%

AI can already do 23% of this job.

#311 / 633

Radiation oncologist

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.

Task	Share	AI	Points
Contouring, fractions and the dose plan. Estimate No public source provides a precise figure. This is our estimate.	16%	48%	+7.7
Clinic, the tumour and what can be irradiated. Estimate No public source provides a precise figure. This is our estimate.	18%	18%	+3.2
Simulation, immobilisation and the machine day. Estimate No public source provides a precise figure. This is our estimate.	16%	22%	+3.5
Side effects, pauses and the patient who cannot take it. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
Board, the surgeon and the medical oncologist. Estimate No public source provides a precise figure. This is our estimate.	18%	14%	+2.5
Signing the plan and the dose that does not erase. Estimate No public source provides a precise figure. This is our estimate.	16%	12%	+1.9
Total	100%		23%

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

IS WORK OVER?

26%

#211 / 633

Last-mile manager

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.

Task	Share	AI	Points
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
Total	100%		26%

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