IS WORK OVER?

Automation index

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

A hoof card comes earlier. Shoeing the horse so it is not lame the next day do not.

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

Task comparison

Farrier

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
Hoof, balance and the animal’s card.
Estimate

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

16%32%+5.1
Trim, nail and the one that will not stand.
Estimate

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

22%8%+1.8
Forge, the made shoe and the trim.
Estimate

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

16%22%+3.5
Lameness, the vet and not blaming the shoe.
Estimate

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

16%28%+4.5
The yard, the owner and the one who does not pay.
Estimate

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

16%18%+2.9
Not lame, and not over-nailing.
Estimate

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

14%12%+1.7
Total100%19%

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

Skills and activities

  • shoe horses
  • balance
  • trim hooves
  • made shoes
  • lameness
  • the forge
  • yards
  • nail

Sources for this job· O*NET 45-2021.00· ESCO/ISCO 6121

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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