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Manufacturing & Production · Updated Aug 2026

Medical Appliance Technicians

Construct, maintain, or repair medical supportive devices such as braces, orthotics and prosthetic devices, joints, arch supports, and other surgical and medical appliances.

JVS 2.0.0-phase4b
AI Exposure
51/100
Moderate

How much of this occupation’s work can be materially affected by current AI systems.

Replacement Risk
43/100
Moderate

How likely exposure is to translate into reduced human demand.

Includes provisional estimates for AI adoption pressure and labour-market resilience. How this is measured

Evidence quality
Confidence82/100
Task coverage87%

Confidence reflects task coverage, mapping and capability-evidence quality, and how much of the score rests on provisional inputs.

Task-level evidence

What is driving the score?

Occupation scores are built from the task mix—not a single prediction about a job title.

JVS 2.0.0-phase4b
TaskImportanceAI impactExposure
Bend, form, and shape fabric or material to conform to prescribed contours of structural components.High
72
Make orthotic or prosthetic devices, using materials such as thermoplastic and thermosetting materials, metal alloys and leather, and hand or power tools.High
69
Read prescriptions or specifications to determine the type of product or device to be fabricated and the materials and tools required.High
70
Cover or pad metal or plastic structures or devices, using coverings such as rubber, leather, felt, plastic, or fiberglass.High
72
Polish artificial limbs, braces, or supports, using grinding and buffing wheels.High
72
Lay out and mark dimensions of parts, using templates and precision measuring instruments.High
72
Fit appliances onto patients, and make any necessary adjustments.High
60
Mix pigments to match patients' skin coloring, according to formulas, and apply mixtures to orthotic or prosthetic devices.High
59
Construct or receive casts or impressions of patients' torsos or limbs for use as cutting and fabrication patterns.High
24
Drill and tap holes for rivets, and glue, weld, bolt, or rivet parts together to form prosthetic or orthotic devices.High
16
Repair, modify, or maintain medical supportive devices, such as artificial limbs, braces, or surgical supports, according to specifications.High
17
Test medical supportive devices for proper alignment, movement, or biomechanical stability, using meters and alignment fixtures.High
18
Most exposed

Where AI can do more

Routine, digitized, and highly repeatable tasks face the greatest pressure.

  1. Bend, form, and shape fabric or material to conform to prescribed contours of structural components.72
  2. Cover or pad metal or plastic structures or devices, using coverings such as rubber, leather, felt, plastic, or fiberglass.72
  3. Polish artificial limbs, braces, or supports, using grinding and buffing wheels.72
  4. Lay out and mark dimensions of parts, using templates and precision measuring instruments.72
Hardest to automate

Where people still matter

These tasks score lowest on automation feasibility—physical presence, judgement, accountability and real-world variability all resist end-to-end automation.

  1. Drill and tap holes for rivets, and glue, weld, bolt, or rivet parts together to form prosthetic or orthotic devices.01
  2. Repair, modify, or maintain medical supportive devices, such as artificial limbs, braces, or surgical supports, according to specifications.02
  3. Test medical supportive devices for proper alignment, movement, or biomechanical stability, using meters and alignment fixtures.03
  4. Construct or receive casts or impressions of patients' torsos or limbs for use as cutting and fabrication patterns.04
  5. Bend, form, and shape fabric or material to conform to prescribed contours of structural components.05
Where else this work leads

Related occupations

Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.

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Beyond AI capability

Adoption and labour-market outlook

Structural factors are kept separate from raw capability so you can see what actually resists automation. Adoption pressure and labour-market resilience are still provisional models—25% of this occupation’s replacement-risk weight rests on them.

Human dependency67
Physical dependency55
Adoption pressure37
Labour-market resilience69
Methodology & sources

O*NET 30.3 occupational data interpreted through the JobsVsAI capability, automation and structural-constraint models.

Confidence82/100
CalculatedAug 21, 2026
Read methodology →