How exposed this work is to automation, shown as ranges with the reasoning and sources.
The short version: this role is less exposed to automation, and a near-term shift looks unlikely.
It is a sourced range, not a verdict, and the detail is below.
Built on O*NET tasks, BLS pay and projections, and peer-reviewed AI-exposure research. Sources shown.
Data snapshot SNAPSHOT-2026-11-06. How it works
AI / softwarerange 6.5 to 30.5
Physical / roboticsrange 23.9 to 47.9
When the change is likely
Largely unaffectedlocal demand growing
What to do about it
Use AI to outpace AI.
Strategies to protect your livelihood, most important first.
1
Stay sharp; urgency is low
This role looks durable. Keep your skills current and watch for shifts in your field.
2
Build a financial buffer
Keep 6 to 12 months of expenses and diversify your income, so a disruption is a setback rather than a catastrophe.
3
Add a recognised credential
A certification or license raises the bar against automation and signals value in a tightening market.
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Which of my tasks are exposed
Confer with clients about their medical histories and problems with stress or pain to determine how massage will be most helpful.
100.0
Massage and knead muscles and soft tissues of the body to provide treatment for medical conditions, injuries, or wellness maintenance.
35.9
Maintain massage areas by restocking supplies or sanitizing equipment.
35.9
Apply finger and hand pressure to specific points of the body.
35.9
Develop and propose client treatment plans that specify which types of massage are to be used.
100.0
Maintain treatment records.
50.0
Assess clients' soft tissue condition, joint quality and function, muscle strength, and range of motion.
35.9
Provide clients with guidance and information about techniques for postural improvement and stretching, strengthening, relaxation, and rehabilitative exercises.
100.0
Longer, orange bars are more automatable; short green bars are resistant.
What is driving my result
lowers risk
raises risk
Task: Confer with clients about their medical histories and problems with stress or pain to determine how massage will be most helpful.
Task: Develop and propose client treatment plans that specify which types of massage are to be used.
Local demand is growing
How this score is calculated
Map Massage Therapists to its standard O*NET task list (8 core tasks).
Score each task for AI/software exposure (Eloundou et al. 2023) and physical/robotics exposure (an O*NET work-context proxy), each 0 to 100.
The two axis scores are the task averages: AI 18.5, robotics 35.9.
The timeline comes from the higher axis (35.9), shifted for local demand (growing), and seniority. It is read against your remaining working years.
Ranges are about ±12 points. A backtest against real BLS employment change shows the risk ranking holds in aggregate, but individual outcomes are predicted weakly, so results are ranges, never a flat verdict.
Sources: O*NET, Eloundou et al. (2023), GPTs are GPTs, O*NET Work Context, BLS CPI-U, BLS OEWS.
Snapshot SNAPSHOT-2026-11-06. Full method and backtest on How it works.