Automation index
How much of a Football coach’s job can AI already do?
A lineup and a clip come earlier. Going out to compete without breaking do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Football coach
22%
AI can already do 22% of this job.
#332 / 633
View rankingFootball coach
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 |
|---|---|---|---|
Lineup, plan and the opponent clip.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Train, the one who is late and the one who hides.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Match, the changes and the one who boils.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Dressing room, the ego and not losing the group.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
The board, the parents and not picking the son under pressure.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Compete, and not breaking.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 22% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- lineups
- opponent clip
- training
- changes
- dressing room
- parents
- pick the side
- match plan
Sources for this job· O*NET 27-2022.00· ESCO/ISCO 3422
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