A Governed AI-Assisted Integrity System

A governed AI-assisted integrity system begins with engineering control of the source information. Before inspection records, design data, corrosion histories or risk assessments are used by artificial intelligence, they must first be reviewed and understood by a competent engineer. AI should not be expected to decide whether incomplete, inconsistent or poorly structured information is suitable for integrity assessment.

With OpenRBI, the engineer sorts, reads and evaluates the available source data. Missing information, conflicting records, uncertain assumptions and inspection gaps are identified before the information is authorised for AI use. This process turns fragmented documents and historical inspection records into structured, traceable and engineering-reviewed knowledge.

Risk-based inspection is an important part of this process, but it is not the final destination. The RBI assessment provides a disciplined method for understanding degradation, inspection effectiveness, probability of failure, consequence and future inspection priorities. It also helps the engineer determine which information is reliable, which conclusions are justified and where further investigation is required.

Once the information has been reviewed and structured, the resulting RBI report can become a trusted input to the company’s AI system. The report provides more than raw data. It contains engineering context, defined terminology, assumptions, limitations, risk findings, inspection priorities and review requirements. This gives the AI system a controlled knowledge source rather than an uncontrolled collection of files.

Engineering must continue to define the boundaries of AI use. This includes deciding which data may be used, which calculations are authoritative, which assumptions are acceptable and which conclusions require human review. The AI system may assist with searching records, comparing equipment, identifying missing fields, detecting inconsistencies and highlighting exceptions, but it should operate within rules established by the organisation and its engineers.

The integrity decision remains an engineering responsibility. AI may accelerate review and improve access to information, but it does not replace professional judgement, equipment knowledge or formal approval. Engineers remain responsible for deciding whether the source information is adequate, whether the analysis is technically sound and whether the recommended inspection or integrity action is appropriate.

OpenRBI therefore acts as a bridge between traditional inspection information and governed corporate AI. It prepares the engineering knowledge so that AI can use it more reliably, transparently and consistently. The objective is not to transfer integrity responsibility to AI, but to create an AI-assisted process in which engineering remains in control from data preparation through to the final integrity decision.