IS WORK OVER?

Automation index

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

A lineup and a clip come earlier. Going out to compete without breaking do not.

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

Task comparison

Football 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
Lineup, plan and the opponent clip.
Estimate

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

16%40%+6.4
Train, the one who is late and the one who hides.
Estimate

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

18%14%+2.5
Match, the changes and the one who boils.
Estimate

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

16%28%+4.5
Dressing room, the ego and not losing the group.
Estimate

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

16%22%+3.5
The board, the parents and not picking the son under pressure.
Estimate

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

18%18%+3.2
Compete, and not breaking.
Estimate

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

16%12%+1.9
Total100%22%

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

Skills and activities

  • lineups
  • opponent clip
  • training
  • changes
  • dressing room
  • parents
  • pick the side
  • match plan

Sources for this job· O*NET 27-2022.00· ESCO/ISCO 3422

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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