Automation index
How much of a Demolition worker’s job can AI already do?
A demolition plan comes earlier. Bringing it down without taking the party wall or anyone do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Demolition worker
19%
AI can already do 19% of this job.
#518 / 633
View rankingDemolition worker
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 |
|---|---|---|---|
Plan, asbestos and prior removal.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
Demolish, cut and the controlled push.EstimateNo public source provides a precise figure. This is our estimate. | 22% | 8% | +1.8 |
Party wall, shore and the neighbour who complains.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Waste, sorting and the tip.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Dust, water and not leaving the street a site.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Not taking the party wall, and signing the takedown.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 10% | +1.4 |
| Total | 100% | 19% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- demolish
- remove asbestos
- shore party walls
- sort waste
- controlled cut
- demolition dust
- the tip
- controlled push
Sources for this job· O*NET 47-2061.00· ESCO/ISCO 7112
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