AI Adoption Can Strengthen NDT Engineering Discipline

By Gleb Tsipursky, PhD

September 01, 2026

Learn Directly From Dr. Gleb Tsipursky at the ASNT Battle of the AI Agents

This NDE Outlook column is authored by Dr. Gleb Tsipursky, who will be returning to ASNT 2026 to lead the second ASNT Battle of the AI Agents on Monday & Tuesday, 12-13 October. In this hands-on workshop, you'll create, test, and refine your solution while learning from peers, judges, and winning teams. Leave knowing how to build with AI, and a chance to win a free registration to ASNT 2027! Registration is open now.

Background

Nondestructive testing (NDT) professionals work at the intersection of speed and consequence. A faster report or cleaner handoff matters, but no efficiency gain justifies weaker traceability, qualification, or expert judgment. ASNT describes NDT [1] as a multidisciplinary profession that protects the safety and reliability of structures, products, and systems without damaging what is examined. That mission should define AI adoption [2] in the field. ASNT's proposed standard on AI and machine learning for nondestructive testing/evaluation (NDT/E) signals a shift from informal experimentation toward disciplined development, validation, deployment, and maintenance.

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