IS WORK OVER?

Automation index

How much of a Office manager’s job can AI already do?

An office inventory comes earlier. The house working without running out of paper do not.

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

Task comparison

Office 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.

TaskShareAIPoints
Vendors, contracts and the inventory.
Estimate

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

18%48%+8.6
Facilities, the air-con and the one who is late.
Estimate

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

16%40%+6.4
Onboarding, keys and the desk.
Estimate

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

16%22%+3.5
Budget, the extra and not overspending.
Estimate

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

16%28%+4.5
Management, the surprise and not leaving the office dark.
Estimate

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

18%14%+2.5
That it works, and not running out of paper.
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

  • office inventory
  • facilities
  • onboarding
  • vendor contracts
  • keys
  • desks
  • office budget
  • air-con

Sources for this job· O*NET 11-3012.00· ESCO/ISCO 1219

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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