Automation index
How much of a Sports physician’s job can AI already do?
A cardiopulmonary test comes earlier. Clearing the return to play and not losing the season do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Sports physician
23%
AI can already do 23% of this job.
#305 / 633
View rankingSports physician
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 |
|---|---|---|---|
CPET, labs and load.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 48% | +7.7 |
Injury, exam and the yes or no to training.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Rehab, injections and the club note.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Anti-doping, certificates and the yearly check.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
The bench, the match and the twisted ankle.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Club pressure and signing return to play.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
- CPET
- rehab injuries
- return to play
- inject athletes
- anti-doping
- fitness certificate
- training load
- sports medicine
Sources for this job· O*NET 29-1229.00· 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