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.

#357 / 763

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?

27%

#185 / 763

QA automation engineer

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
Test, the selector and the flake. Estimate No public source provides a precise figure. This is our estimate.	18%	48%	+8.6
Pipeline, the green and the one that lies. Estimate No public source provides a precise figure. This is our estimate.	16%	40%	+6.4
Bug, the repro and not closing it blind. Estimate No public source provides a precise figure. This is our estimate.	16%	22%	+3.5
Data, the environment and not sharing prod. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
The developer, the rush and not skipping the one that fails. Estimate No public source provides a precise figure. This is our estimate.	18%	14%	+2.5
Catch the bug, and not painting a lying green. Estimate No public source provides a precise figure. This is our estimate.	16%	12%	+1.9
Total	100%		27%

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