IS WORK OVER?

Automation index

How much of a Tourist-office officer’s job can AI already do?

A map and a leaflet come earlier. The visitor leaving happy, not lost, do not.

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

Task comparison

Tourist-office officer

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
Map, diary and the counter.
Estimate

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

18%48%+8.6
The one with no language, the one who argues and the one with no booking.
Estimate

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

16%40%+6.4
Events, capacity and the one that cancels.
Estimate

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

16%22%+3.5
Data, survey and not inflating visitors.
Estimate

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

16%28%+4.5
The council, the shops and not only selling the centre.
Estimate

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

18%14%+2.5
Happy, and not lost.
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

  • tourist counter
  • maps
  • events diary
  • capacity
  • surveys
  • bookings
  • visitors
  • the council

Sources for this job· O*NET 41-3041.00· ESCO/ISCO 4221

Data 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.

TaskShareAIPoints
Models, lineage and the catalogue.
Estimate

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

18%52%+9.4
Pipelines, quality and the data contract.
Estimate

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

16%40%+6.4
The analyst who finds nothing and the mess.
Estimate

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

16%22%+3.5
Privacy, retention and the field you cannot keep.
Estimate

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

16%28%+4.5
The business, shadow IT and not building another lake.
Estimate

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

18%14%+2.5
That it gets used, and not letting raw data rot.
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

  • 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

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