Automation index
How much of a Dry cleaner’s job can AI already do?
A stain card comes earlier. Lifting the stain without eating the colour do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Dry cleaner
22%
AI can already do 22% of this job.
#360 / 623
View rankingDry cleaner
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 |
|---|---|---|---|
Card, fibre and pretreatment.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Machine, solvent and the delicate garment.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Press, the finish and the one that marks.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Job, the groom and the one who wants it now.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
The old stain and not promising miracles.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Lift the stain, and not eating the colour.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
- pretreat stains
- solvents
- press
- delicates
- job cards
- finish
- fibres
- old stains
Sources for this job· O*NET 51-6011.00· ESCO/ISCO 9121
IS WORK OVER?
Data engineer
31%
#36 / 623
View rankingData 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 pipelines, models and orchestration.EstimateNo public source provides a precise figure. This is our estimate. | 24% | 50% | +12 |
Write SQL, Spark and data tests.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 45% | +8.1 |
Incidents, quality and lineage in production.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Talk to analysts and negotiate data contracts.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Cloud cost, permissions and PII.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 15% | +2.1 |
Decide architecture and technical debt.EstimateNo public source provides a precise figure. This is our estimate. | 12% | 20% | +2.4 |
| Total | 100% | 31% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Design pipelines, models and orchestration
- Write SQL, Spark and data tests
- Cloud cost, permissions and PII
- Decide architecture and technical debt
- ingeniero de datos
- data engineer
- etl
Sources for this job· O*NET 15-1243.00· ESCO/ISCO 2511