IS WORK OVER?

Automation index

How much of a Massage therapist’s job can AI already do?

A chart and a booking come earlier. Hands on a trapezius, and not doing harm, do not.

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

Task comparison

Massage therapist

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
Bookings, charts and consent.
Estimate

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

14%32%+4.5
Massage, pressure and tissue work.
Estimate

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

24%8%+1.9
Assess complaint, contraindication and referral.
Estimate

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

16%18%+2.9
Explain posture and exercises.
Estimate

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

16%22%+3.5
Couch hygiene, oils and the room.
Estimate

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

16%14%+2.2
The therapist’s body and not injuring anyone.
Estimate

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

14%16%+2.2
Total100%17%

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

Skills and activities

  • Bookings, charts and consent
  • Massage, pressure and tissue work
  • Explain posture and exercises
  • Couch hygiene, oils and the room
  • masajista
  • massage therapist

Sources for this job· O*NET 31-9011.00· ESCO/ISCO 3255

Station master

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
Graph, orders and the station log.
Estimate

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

16%40%+6.4
Platforms, the crossing and the late train.
Estimate

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

18%14%+2.5
Staff, shifts and the ticket-office gap.
Estimate

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

16%32%+5.1
Incident, passengers and the PA.
Estimate

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

16%22%+3.5
Works, closures and leaving nobody on the platform.
Estimate

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

18%18%+3.2
That they do not meet, and signing the graph.
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

  • train graph
  • orders
  • platforms
  • ticket office
  • PA
  • line crossings
  • station shifts
  • station logs

Sources for this job· O*NET 53-4031.00· ESCO/ISCO 4323

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