AI‑Integrated Industrial Systems: Competence Migration, Safety Architecture, and Knowledge Extinction Risk"

Industrial systems are undergoing a structural transition from labour‑dependent mechanical control to AI‑integrated autonomous decision architectures. This paper unifies two analytical frameworks — Industrial Equipment Evolution and Knowledge Extinction Risk (KER) — into a single model describing competence migration, safety paradigm shifts, and irreversible knowledge loss dynamics in Phase‑5 AI‑ready environments. We demonstrate that competence does not disappear under automation; it migrates from human operators into system architecture, creating new failure modes rooted in model error, context blindness, and verification gaps. Empirical evidence from aviation, maritime navigation, nuclear operations, manufacturing, and surgical robotics confirms that automation eliminates the practice context required for maintaining tacit expertise, producing measurable skill decay and structural knowledge extinction. We propose a unified safety and competence framework for AI‑integrated industries, emphasising the irreducible human function of interpretive verification and the need for new regulatory architectures aligned with autonomous decision systems.