As AI becomes increasingly capable of producing engineering documentation, calculations, software, and technical recommendations, I believe we need to distinguish four very different things:
The ability to generate an engineering result.
The evidence supporting its technical correctness.
The authority to approve that result.
The authorization to release it for use.
These are not interchangeable.
A technically convincing answer is not necessarily a verified answer.
A completed task is not necessarily an approved deliverable.
My ongoing work on Engineering AI Trust examines how engineering organizations can establish traceability, identify missing information, document uncertainty, and maintain accountable human approval and the related structure.
The objective is not to slow engineering down. It is to make AI-assisted engineering faster without surrendering control over what we accept as correct.
Our working principle is simple: build a trustable structure before implementing AI. That is easier said than done and full of nuances.
The frameworks and measurement methods involved remain under development and are being prepared for structured independent validation
I would be interested in hearing how other engineering organizations are approaching this distinction.
