IS WORK OVER?

Automation index

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

A dive plan comes earlier. Working below and coming up whole do not.

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

Task comparison

Commercial diver

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
Plan, tables and the day’s gas.
Estimate

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

16%32%+5.1
Bottom, tool and the one who snags.
Estimate

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

24%6%+1.4
Comms, the tender and stopping in time.
Estimate

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

16%22%+3.5
Inspection, wet weld or cut.
Estimate

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

16%28%+4.5
Current, zero vis and not losing the buddy.
Estimate

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

14%18%+2.5
Come up whole, and not skipping decompression.
Estimate

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

14%10%+1.4
Total100%18%

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

Skills and activities

  • dive plan
  • decompression tables
  • wet weld
  • tender
  • zero vis
  • underwater cut
  • dive gas
  • the bottom

Sources for this job· O*NET 49-9092.00· ESCO/ISCO 7541

Last-mile manager

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
Zones, capacity and route cuts.
Estimate

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

16%44%+7
KPIs, first attempt and incidents.
Estimate

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

16%36%+5.8
The courier, the lobby and the one who will not open.
Estimate

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

18%16%+2.9
Peaks, rain and hiring too many or too few.
Estimate

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

16%28%+4.5
The angry customer and not dressing delivered.
Estimate

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

18%18%+3.2
Cover the peak, and not leaving the neighbourhood orphaned.
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

  • delivery zones
  • first attempt
  • delivery KPIs
  • last-mile peaks
  • lobbies
  • delivery incidents
  • courier capacity
  • cut routes

Sources for this job· O*NET 11-3071.00· ESCO/ISCO 1324

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