Automation index
How much of a Props master’s job can AI already do?
A props list comes earlier. The object being there, working and not breaking on stage do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Props master
19%
AI can already do 19% of this job.
#479 / 633
View rankingProps master
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 |
|---|---|---|---|
List, references and the budget.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
Make, adapt and the one that will not fit the hand.EstimateNo public source provides a precise figure. This is our estimate. | 22% | 8% | +1.8 |
Rehearsal, the change and the one that vanishes.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Show, tables and the preset.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The actor, the whim and not improvising the weapon.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
That it is there, and not breaking on stage.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 12% | +1.7 |
| Total | 100% | 19% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- props lists
- presets
- adapt objects
- props rehearsals
- show tables
- stage weapons
- references
- props budget
Sources for this job· O*NET 27-1027.00· ESCO/ISCO 3435
IS WORK OVER?
Data architect
28%
#83 / 633
View rankingData architect
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 |
|---|---|---|---|
Models, lineage and the catalogue.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Pipelines, quality and the data contract.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
The analyst who finds nothing and the mess.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Privacy, retention and the field you cannot keep.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The business, shadow IT and not building another lake.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
That it gets used, and not letting raw data rot.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 28% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- model data
- lineage
- data catalogue
- data contracts
- pipeline quality
- retention
- data lakes
- privacy
Sources for this job· O*NET 15-1243.00· ESCO/ISCO 2511