Automation index
How much of a Golf professional’s job can AI already do?
A swing clip comes earlier. Changing the strike so the handicap comes down do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Golf professional
22%
AI can already do 22% of this job.
#369 / 633
View rankingGolf professional
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 |
|---|---|---|---|
Swing, clip and the plan.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Course, the pupil and the one who does not listen.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Putting, the green and patience.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Handicap, the event and not inflating.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
The shop, the club and not selling smoke.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Bring the handicap down, and not breaking the swing.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
- swing
- strike clip
- putting
- handicap
- the green
- events
- clubs
- the range
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