Automation index
How much of a Executive housekeeper’s job can AI already do?
A roster and a checklist come earlier. A hundred rooms out on time does not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Executive housekeeper
21%
AI can already do 21% of this job.
#431 / 643
View rankingExecutive housekeeper
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 |
|---|---|---|---|
Roster, checklists and linen logs.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 40% | +7.2 |
Rounds, standards and VIP rooms.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Room team, shifts and conflict.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Front desk, maintenance and complaints.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Inventory, minibar and lost-and-found.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 16% | +2.6 |
Not handing a dirty room to a guest.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 21% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Roster, checklists and linen logs
- Rounds, standards and VIP rooms
- Room team, shifts and conflict
- Front desk, maintenance and complaints
- Inventory, minibar and lost-and-found
- Not handing a dirty room to a guest
- gobernanta
- ama de llaves
- executive housekeeper
Sources for this job· O*NET 37-1011.00· ESCO/ISCO 5151
IS WORK OVER?
Last-mile manager
26%
#216 / 643
View rankingLast-mile manager
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 |
|---|---|---|---|
Zones, capacity and route cuts.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 44% | +7 |
KPIs, first attempt and incidents.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 36% | +5.8 |
The courier, the lobby and the one who will not open.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 16% | +2.9 |
Peaks, rain and hiring too many or too few.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The angry customer and not dressing delivered.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Cover the peak, and not leaving the neighbourhood orphaned.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 26% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- delivery zones
- first attempt
- delivery KPIs
- last-mile peaks
- lobbies
- delivery incidents
- courier capacity
- cut routes
Sources for this job· O*NET 11-3071.00· ESCO/ISCO 1324