Automation index
How much of a Museum educator’s job can AI already do?
A teaching sheet comes earlier. Thirty schoolchildren in front of the work, actually looking, do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Museum educator
24%
AI can already do 24% of this job.
#264 / 633
View rankingMuseum educator
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 |
|---|---|---|---|
Sheets, routes and the teaching kit.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 44% | +7 |
The tour, the group that will not quiet, and the work.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 12% | +2.2 |
Workshops, families and Sunday at the museum.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
School, bookings and the missing mediator.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Access, the public who do not come in, and adapting.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
That they actually look, and not reciting the label.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 24% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- school tours
- teaching sheets
- museum workshops
- cultural mediation
- group bookings
- access
- families at the museum
- learning routes
Sources for this job· O*NET 25-4012.00· ESCO/ISCO 2621
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