The Governance Gap Is Real

LinkedIn Post 6: The Governance Gap Is Real

Three conversations I've had this week:

Organization A: "Our AI recommends deferring 40% of scheduled inspections. We're saving money."

Me: "Who validates the recommendations?"

Them: "Our maintenance team checks them informally."

Organization B: "We're using AI to optimize inspection scheduling."

Me: "How do you ensure sensor reliability?"

Them: "The sensors are industrial standard. They should be fine."

Organization C: "We defer inspections based on AI recommendations."

Me: "What happens if a vessel fails after an AI-deferred inspection?"

Them: "We haven't really thought about that."

These are not edge cases. These are mainstream organizations using AI in pressure vessel inspection without governance frameworks.

The governance gap is real. And it's growing as more organizations adopt predictive maintenance systems.

Here's what needs to happen:

1. AI systems are formally integrated into written schemes of examination

2. Competent persons are trained to understand and validate recommendations

3. Sensors are certified as reliable before their data influences decisions

4. Incident tracking captures failures linked to deferred inspections

5. Clear procedures define when AI recommendations are used and how they're validated

This is APMGA. It's not a regulatory requirement yet. But as incidents accumulate, it will become one.

The question is: Will your organization implement it proactively, or reactively after an incident?