IS WORK OVER?

Automation index

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

A deposit model comes earlier. Going down and not leaving an unsafe face does not.

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

Task comparison

Mining engineer

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
Model deposit, blast and rates.
Estimate

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

16%40%+6.4
Drawings, permits and mining plans.
Estimate

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

16%28%+4.5
Face, safety and ventilation.
Estimate

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

18%14%+2.5
Plant, contractors and output.
Estimate

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

16%22%+3.5
Restoration, waste and regulation.
Estimate

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

18%16%+2.9
Not leaving a miner below.
Estimate

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

16%12%+1.9
Total100%22%

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

Skills and activities

  • Model deposit, blast and rates
  • Drawings, permits and mining plans
  • Face, safety and ventilation
  • Plant, contractors and output
  • Restoration, waste and regulation
  • Not leaving a miner below
  • ingeniero de minas
  • mining engineer

Sources for this job· O*NET 17-2151.00· ESCO/ISCO 2146

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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