Automation index
How much of a Hospital porter’s job can AI already do?
A transfer ping comes earlier. Moving someone on drips and not dropping them does not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Hospital porter
16%
AI can already do 16% of this job.
#611 / 643
View rankingHospital porter
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 |
|---|---|---|---|
Alerts, destinations and transfer notes.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Trolleys, chairs and moving patients.EstimateNo public source provides a precise figure. This is our estimate. | 24% | 8% | +1.9 |
Theatre, mortuary and hospital stores.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
Dealing with families, discharges and waits.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Support nursing and bay safety.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 22% | +3.1 |
Shifts, physical load and not hurting your back.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 14% | +2 |
| Total | 100% | 16% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Alerts, destinations and transfer notes
- Trolleys, chairs and moving patients
- Theatre, mortuary and hospital stores
- Support nursing and bay safety
- celador
- camillero
- hospital porter
Sources for this job· O*NET 31-1132.00· ESCO/ISCO 5329
IS WORK OVER?
Prompt engineer
34%
#21 / 643
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