IS WORK OVER?

Automation index

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

A screening protocol comes earlier. Calling fit or not and facing the company do not.

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

Task comparison

Occupational physician

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
Screenings, protocols and the work history.
Estimate

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

18%52%+9.4
Fit notes, restrictions and PPE.
Estimate

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

16%40%+6.4
The hard case, the one who cannot, and the company pushing.
Estimate

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

18%18%+3.2
Risk surveillance, sick leave and return.
Estimate

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

16%28%+4.5
Inspectorate, mutual and coordination with H&S.
Estimate

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

16%22%+3.5
Medical secrecy and signing fit for work.
Estimate

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

16%14%+2.2
Total100%29%

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

Skills and activities

  • occupational screening
  • fit for work
  • health surveillance
  • work restrictions
  • return to work
  • occupational medicine
  • work history
  • medical secrecy

Sources for this job· O*NET 29-1229.00· ESCO/ISCO 2212

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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