Automation index
How much of a Merchandiser’s job can AI already do?
A planogram comes earlier. A shelf that sells without looking empty do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Merchandiser
22%
AI can already do 22% of this job.
#353 / 633
View rankingMerchandiser
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 |
|---|---|---|---|
Planogram, facings and the shelf.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Store, replenish and the one who will not follow the plan.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Promo, the extra and the one that falls.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Data, sell-out and not inflating facings.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
The store manager, the space and fighting for the gap.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
That the shelf sells, and not empty.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
- planograms
- facings
- the shelf
- sell-out
- promos
- replenish
- store space
- gaps
Sources for this job· O*NET 41-9011.00· ESCO/ISCO 5223
IS WORK OVER?
Mobile developer
28%
#92 / 633
View rankingMobile developer
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 |
|---|---|---|---|
Screens, API and offline state.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Store review, crashlytics and ANRs.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Real device, the notch and fragmented Android.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
CI, tests and the week's release.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Product, the redesign and not breaking what people use.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
That it does not crash, and not ignoring the one-star.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
- build apps
- ship to stores
- crashlytics
- offline state
- ANRs
- mobile tests
- fragmented Android
- store review
Sources for this job· O*NET 15-1252.00· ESCO/ISCO 2514