IS WORK OVER?

Automation index

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

An enclosure protocol comes earlier. Going in, feeding and not losing an animal do not.

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

Task comparison

Zookeeper

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
Protocol, ration and the enclosure log.
Estimate

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

16%32%+5.1
Go in, clean and the one that will not come off.
Estimate

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

22%8%+1.8
Enrichment, the public and not teaching badly.
Estimate

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

16%22%+3.5
Vet, the sign and calling it in time.
Estimate

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

16%28%+4.5
Escape, the protocol and not improvising.
Estimate

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

16%18%+2.9
Not losing an animal, and not skipping the lock.
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

  • enclosures
  • zoo rations
  • enrichment
  • escape protocol
  • vet log
  • lock-up
  • enclosure clean
  • the public

Sources for this job· O*NET 39-2021.00· ESCO/ISCO 5164

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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