IS WORK OVER?

Automation index

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

A camera plan comes earlier. Seeing the face, not the wall opposite, do not.

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

Task comparison

CCTV technician

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, FOV and the recorder.
Estimate

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

16%40%+6.4
Fit, focus and the backlight that blinds.
Estimate

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

18%14%+2.5
Network, PoE and the disk that fills.
Estimate

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

16%32%+5.1
Data-protection law, signs and the client who wants the whole street.
Estimate

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

16%22%+3.5
Residents, the porter and the illegal angle.
Estimate

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

18%18%+3.2
See the face, and not recording extra.
Estimate

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

16%12%+1.9
Total100%23%

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

Skills and activities

  • focus cameras
  • FOV
  • PoE
  • recorders
  • data-protection signs
  • lawful angles
  • recording disks
  • camera plan

Sources for this job· O*NET 49-2098.00· ESCO/ISCO 7412

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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