IS WORK OVER?

Automation index

How much of a Hotel concierge’s job can AI already do?

A booking and a map come earlier. A table at ten, and calming someone, do not.

This percentage does not predict how many people will lose their jobs.

Task comparison

Hotel concierge

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
Bookings, maps and recommendations.
Estimate

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

16%40%+6.4
Desk, bags and difficult guests.
Estimate

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

20%12%+2.4
Restaurants, tickets and transport.
Estimate

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

16%22%+3.5
Logs, shifts and front-desk coordination.
Estimate

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

16%28%+4.5
Neighbourhood, vendors and errands.
Estimate

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

16%16%+2.6
Not leaving a guest stranded at two in the morning.
Estimate

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

16%14%+2.2
Total100%22%

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

Skills and activities

  • Bookings, maps and recommendations
  • Desk, bags and difficult guests
  • Restaurants, tickets and transport
  • Logs, shifts and front-desk coordination
  • Neighbourhood, vendors and errands
  • conserje
  • concierge
  • portero de hotel

Sources for this job· O*NET 43-4081.00· ESCO/ISCO 4224

Mobile 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.

TaskShareAIPoints
Screens, API and offline state.
Estimate

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

18%52%+9.4
Store review, crashlytics and ANRs.
Estimate

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

16%40%+6.4
Real device, the notch and fragmented Android.
Estimate

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

16%22%+3.5
CI, tests and the week's release.
Estimate

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

16%28%+4.5
Product, the redesign and not breaking what people use.
Estimate

No 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.
Estimate

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

16%12%+1.9
Total100%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

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