IS WORK OVER?

Automation index

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

A stroke pattern comes earlier. Getting them on court without wrecking the shoulder do not.

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

Task comparison

Tennis coach

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
Pattern, rally and the plan.
Estimate

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

16%32%+5.1
Court, the one who hides and the one who overhits.
Estimate

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

22%8%+1.8
Competition, the needle and the one who throws the racquet.
Estimate

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

16%22%+3.5
Shoulder, load and not rushing the event.
Estimate

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

16%28%+4.5
Parents, the ranking and not burning the child.
Estimate

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

16%18%+2.9
On court, and the shoulder whole.
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

  • rally
  • stroke patterns
  • court
  • shoulder
  • ranking
  • racquet
  • parents
  • training load

Sources for this job· O*NET 27-2022.00· ESCO/ISCO 3422

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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