Automation index
How much of a Packaging engineer’s job can AI already do?
A 3D prototype comes earlier. Surviving transport and opening on the shelf do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Packaging engineer
27%
AI can already do 27% of this job.
#161 / 623
View rankingPackaging 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 |
|---|---|---|---|
Spec, 3D and the drop test.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
The packing line and the one that will not fit.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Material, recyclability and unit cost.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 36% | +5.8 |
Supplier, die and pack colour.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Marketing, legal and not lying on the pack.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
That it survives the trip, and not oversizing the plastic.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 27% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- design packs
- drop test
- packing line
- recyclability
- die-cut
- unit cost
- pack spec
- 3D prototype
Sources for this job· O*NET 17-2112.00· ESCO/ISCO 2141
IS WORK OVER?
Data architect
28%
#83 / 623
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