IS WORK OVER?

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

Executive 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.

TaskShareAIPoints
Roster, checklists and linen logs.
Estimate

No public source provides a precise figure. This is our estimate.

18%40%+7.2
Rounds, standards and VIP rooms.
Estimate

No public source provides a precise figure. This is our estimate.

18%14%+2.5
Room team, shifts and conflict.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Front desk, maintenance and complaints.
Estimate

No public source provides a precise figure. This is our estimate.

16%18%+2.9
Inventory, minibar and lost-and-found.
Estimate

No public source provides a precise figure. This is our estimate.

16%16%+2.6
Not handing a dirty room to a guest.
Estimate

No public source provides a precise figure. This is our estimate.

16%14%+2.2
Total100%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

Hydraulic 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.

TaskShareAIPoints
Hydrology, flows and the floodplain model.
Estimate

No public source provides a precise figure. This is our estimate.

18%48%+8.6
Field, section and what LiDAR misses.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Drainage works, pumps and the outfall.
Estimate

No public source provides a precise figure. This is our estimate.

16%36%+5.8
Water permits and the river authority.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
The flood, the village and the yes to the channel.
Estimate

No public source provides a precise figure. This is our estimate.

18%14%+2.5
That it does not flood, and not trusting the model alone.
Estimate

No public source provides a precise figure. This is our estimate.

16%12%+1.9
Total100%27%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • model floodplains
  • flows
  • drainage
  • channel works
  • water permits
  • pumps
  • channel sections
  • river authority

Sources for this job· O*NET 17-2051.00· ESCO/ISCO 2142

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