Structural Limits of Installation-Time Integrity Assurance: A Lifecycle-Based Accountability Framework for Over-the-Air-Enabled Physical AI Systems

Installation-time integrity assurance is widely used as a foundational trust mechanism in over-the-air (OTA) software update ecosystems. By verifying cryptographic authenticity and artifact immutability at deployment, such mechanisms establish a provable baseline of artifact integrity. However, in physical AI systems operating in dynamic and context-dependent environments, it is not sufficient to assume that deployment-time verification alone guarantees semantic correctness during execution. This paper demonstrates that deployment-bound sufficiency does not necessarily hold under dynamic runtime conditions, particularly in systems where behavior emerges from interaction with dynamic physical environments. We establish a structural separation, showing that satisfaction of installation-time integrity does not necessarily imply execution-time behavioral correctness. Even when deployed artifacts remain authentic and unmodified, contextual interaction and runtime control dynamics may induce behavior that violates intended safety semantics. To address this structural limitation, we introduce the Lifecycle Integrity and Accountability Coupling (LIAC) framework. LIAC reframes integrity assurance as a lifecycle-aligned accountability architecture rather than a static deployment predicate. By preserving lightweight, stage-aligned evidence across creation, distribution, installation, execution, and governance phases, LIAC enables structured post-incident localization of responsibility without requiring continuous runtime monitoring. Together, these results provide a formal foundation for understanding the limits of installation-centric integrity models and present a scalable accountability framework for OTA-enabled physical AI systems.