IS WORK OVER?

Automation index

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

A log and a checklist come earlier. Scrubbing a bathroom, a night shift, and a stain that will not lift do not.

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

Task comparison

Cleaner

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
Logs, checklists and product orders.
Estimate

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

14%32%+4.5
Scrubber-driers and dosing.
Estimate

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

12%22%+2.6
Mop, vacuum, disinfect and restock.
Estimate

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

26%10%+2.6
Waste, linen and sensitive areas.
Estimate

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

16%12%+1.9
Shifts, keys and dealing with users.
Estimate

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

16%14%+2.2
Surprises: vomit, works, a complaint.
Estimate

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

16%16%+2.6
Total100%16%

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

Skills and activities

  • Logs, checklists and product orders
  • Scrubber-driers and dosing
  • Mop, vacuum, disinfect and restock
  • Waste, linen and sensitive areas
  • Shifts, keys and dealing with users
  • Surprises: vomit, works, a complaint
  • limpiador
  • limpiadora
  • personal de limpieza
  • cleaner

Sources for this job· O*NET 37-2011.00· ESCO/ISCO 9112

Agile coach

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
Boards, metrics and the cadence design.
Estimate

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

16%40%+6.4
The real retro and the elephant in the room.
Estimate

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

18%14%+2.5
Train, unblock and the manager who will not let go.
Estimate

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

16%32%+5.1
Scale, dependencies and fake agile.
Estimate

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

16%28%+4.5
Conflict, power and not selling extra frameworks.
Estimate

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

18%18%+3.2
That they stop faking it, and not inflating velocity.
Estimate

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

16%14%+2.2
Total100%24%

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

Skills and activities

  • retros
  • agile cadence
  • unblock teams
  • flow metrics
  • fake agile
  • agile training
  • dependencies
  • velocity

Sources for this job· O*NET 13-1111.00· ESCO/ISCO 2421

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