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?
Radiation oncologist
23%
AI can already do 23% of this job.
#311 / 633
View rankingRadiation oncologist
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.
| Task | Share | AI | Points |
|---|---|---|---|
Contouring, fractions and the dose plan.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 48% | +7.7 |
Clinic, the tumour and what can be irradiated.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Simulation, immobilisation and the machine day.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Side effects, pauses and the patient who cannot take it.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Board, the surgeon and the medical oncologist.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Signing the plan and the dose that does not erase.EstimateNo 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
Skills and activities
- contouring
- plan radiotherapy
- dosimetry
- RT simulation
- fractions
- tumour board
- radiation effects
- immobilise the patient
Sources for this job· O*NET 29-1224.00· ESCO/ISCO 2212
IS WORK OVER?
Prompt engineer
34%
#21 / 633
View rankingPrompt engineer
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.
| Task | Share | AI | Points |
|---|---|---|---|
Design prompts, tools and chains.EstimateNo public source provides a precise figure. This is our estimate. | 24% | 58% | +13.9 |
Evals, datasets and regressions.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Integrate with product and safety limits.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Talk to the business about a good output.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Watch hallucinations, bias and cost.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 20% | +2.8 |
Decide what the model gets, and what it does not.EstimateNo public source provides a precise figure. This is our estimate. | 12% | 16% | +1.9 |
| Total | 100% | 34% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Design prompts, tools and chains
- Evals, datasets and regressions
- Integrate with product and safety limits
- Talk to the business about a good output
- Watch hallucinations, bias and cost
- prompt engineer
- ingeniero de prompts
- llm engineer
Sources for this job· O*NET 15-1252.00· ESCO/ISCO 2512