Engineering & ArchitectureO*NET: 17-3029.01
Will AI Replace Non-Destructive Testing Specialists?
Test the safety of structures, vehicles, or vessels using x-ray, ultrasound, fiber optic or related equipment.
60out of 100
High Risk
AI Risk Score
60/100
Risk Level
High
Job Zone
2/5
Entry
Total Tasks Analyzed
15
🤖 What AI Can Do
- ▸Interpret or evaluate test results in accordance with applicable codes, standards, specifications, or procedures.
- ▸Prepare reports on non-destructive testing results.
- ▸Document non-destructive testing methods, processes, or results.
👤 What Requires Humans
- ▸Examine structures or vehicles such as aircraft, trains, nuclear reactors, bridges, dams, and pipelines, using non-destructive testing techniques.
- ▸Supervise or direct the work of non-destructive testing trainees or staff.
- ▸Identify defects in concrete or other building materials, using thermal or infrared testing.
Task Breakdown
🤖AI Can Automate (3)
- Interpret or evaluate test results in accordance with applicable codes, standards, specifications, or procedures.
- Prepare reports on non-destructive testing results.
- Document non-destructive testing methods, processes, or results.
👤Requires Humans (3)
- Examine structures or vehicles such as aircraft, trains, nuclear reactors, bridges, dams, and pipelines, using non-destructive testing techniques.
- Supervise or direct the work of non-destructive testing trainees or staff.
- Identify defects in concrete or other building materials, using thermal or infrared testing.
⚡AI-Assisted (9)
- Interpret the results of all methods of non-destructive testing (NDT), such as acoustic emission, electromagnetic, leak, liquid penetrant, magnetic particle, neutron radiographic, radiographic, thermal or infrared, ultrasonic, vibration analysis, and visual testing.
- Identify defects in solid materials, using ultrasonic testing techniques.
- Make radiographic images to detect flaws in objects while leaving objects intact.
- Select, calibrate, or operate equipment used in the non-destructive testing of products or materials.
- Visually examine materials, structures, or components for signs of corrosion, metal fatigue, cracks, or other flaws, using tools and equipment such as endoscopes, closed-circuit television systems, and fiber optics.
- Produce images of objects on film, using radiographic techniques.
- Conduct liquid penetrant tests to locate surface cracks by coating objects with fluorescent dyes, cleaning excess penetrant, and applying developer.
- Map the presence of imperfections within objects, using sonic measurements.
Key Skills Analysis
Reading ComprehensionAI-Vulnerable
Importance: 3.88/5.00
Quality Control AnalysisAI-Vulnerable
Importance: 3.88/5.00
Active Listening
Importance: 3.62/5.00
Critical ThinkingAI-Resistant
Importance: 3.50/5.00
Monitoring
Importance: 3.38/5.00
WritingAI-Vulnerable
Importance: 3.25/5.00
Active LearningAI-Resistant
Importance: 3.25/5.00
Operations MonitoringAI-Vulnerable
Importance: 3.25/5.00
Speaking
Importance: 3.12/5.00
MathematicsAI-Vulnerable
Importance: 3.12/5.00
Learning Strategies
Importance: 3.12/5.00
Complex Problem SolvingAI-Resistant
Importance: 3.12/5.00
Operation and Control
Importance: 3.12/5.00
Judgment and Decision MakingAI-Resistant
Importance: 3.12/5.00
Systems AnalysisAI-Vulnerable
Importance: 3.12/5.00
Related Occupations
Aerospace Engineering and Operations Technologists and Technicians
67/100 — High Risk
Calibration Technologists and Technicians
10/100 — Very Low Risk
Mechanical Engineering Technologists and Technicians
60/100 — High Risk
Automotive Engineering Technicians
60/100 — High Risk
Electrical and Electronic Engineering Technologists and Technicians
86/100 — Critical Risk
Future-Proof Your Career
Whether AI poses a high or low risk to your role, staying ahead means continuous learning. Explore courses to build AI-resistant skills.
Frequently Asked Questions
Based on our analysis, Non-Destructive Testing Specialists have a high risk of AI replacement with a score of 60/100. Many routine tasks in this role can be automated, but human oversight remains important.
Last updated: 2026-03-28· Data from O*NET 30.2 & Frey/Osborne automation research