IS WORK OVER?

Automation index

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

An ETA comes earlier. Clearing the ship without extra demurrage do not.

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

Task comparison

Ship agent

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
ETA, berth and port services.
Estimate

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

16%44%+7
Clearance, crew and the crew change.
Estimate

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

16%36%+5.8
The master, the terminal and the window clash.
Estimate

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

18%16%+2.9
Invoices, disbursements and the owner’s account.
Estimate

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

16%28%+4.5
The inspection, the delay and not losing the slot.
Estimate

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

18%18%+3.2
No extra demurrage, and the ship cleared.
Estimate

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

16%14%+2.2
Total100%26%

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

Skills and activities

  • ETAs
  • berths
  • ship clearance
  • crew changes
  • disbursements
  • terminal windows
  • owner’s accounts
  • port inspections

Sources for this job· O*NET 43-5011.00· ESCO/ISCO 3331

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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