Industry
Critical Infrastructure
AI governance for environments where operational failures have cascading consequences.
Who in Critical Infrastructure benefits from deterministic AI governance — and what they're hearing from skeptics.
Common Objections
Our operational technology environment is too specialized for general AI governance tools. Kenshiki isn't a general governance overlay. It verifies AI emissions against your operational data — maintenance records, sensor feeds, control system states — before they reach decision points.
Adding verification layers to operational AI could introduce latency that affects safety-critical systems. Verification latency is bounded and deterministic. For safety-critical paths, Kenshiki operates in parallel — flagging unverified emissions without blocking time-critical operations.
We already have SCADA and ICS security tools that monitor our control systems. OT security tools monitor network traffic and control system behavior. Kenshiki addresses a different vector: verifying AI-generated recommendations before they enter the control loop.
Questions to Consider
- Can you trace every AI-generated operational recommendation back to the sensor data, maintenance records, and control system states that informed it?
- How do you prevent unverified AI assessments from influencing safety-critical control decisions?
- What is your audit trail for demonstrating to NERC, TSA, or NRC inspectors how AI systems influenced operational decisions?
- How do you enforce authorization boundaries around AI systems that can influence control system behavior?
- Can your incident response team reconstruct the full AI decision chain during a post-incident root cause analysis?