Where AI governance meets operational reality.

PHYSICAL AI

When AI can act, evidence must follow the action.

Physical consequences extend the question beyond a model output. An examination may need to establish who authorized an action, what constrained execution, which system state was active and how override or recovery was evidenced.

ACTION BOUNDARY

Control the transition from decision to effect.

The examination follows the point where an AI decision can change an actuator, environment or other physical state. Authorization, policy gates, vetoes and override paths belong in the evidence record.

EXAMINATION QUESTIONS

Four records at the point of consequence.

The scope depends on the specific system and action pathway.

Authority

What authorized the action?

Boundary

What constrained, denied or vetoed execution?

State

Which version, configuration and operating state produced it?

Recovery

What records show containment, override or return to service?

FRAMEWORK CONTEXT

PAI-SF™ provides the security architecture.

The Physical AI Security Framework uses Kinetic Zero Trust principles across sensing, decision-making, authorization and actuation. Its published control text establishes the applicable version and scope.

DISTINCT INTERFACES

Security assurance does not replace functional safety.

Sector-specific approval, functional-safety obligations and operational authorization remain separate interfaces. A bounded examination cannot stand in for them without an explicitly established basis.

DISCUSS A SYSTEM

Bring one physical action path and its records.

A useful starting question identifies the consequential action, the authority boundary and the available telemetry or decision record.