Does the Inertia of an Artificial Intelligence System Depend Upon Its Capability-Energy Content?

This paper investigates whether the capability inertia of an artificial intelligence system depends upon its capability-energy content. Building upon previously developed capability-frame transformations and the transformation law for capability-signal energy, the paper considers an artificial intelligence system emitting equal capability signals in opposite directions. Under conservation of generalized capability energy and in the low transformation-rate limit, the analysis yields the relation ΔE_C = c_A²Δm_A between a change in dynamical capability energy and a change in capability inertia. The result is explicitly distinguished from physical mass-energy equivalence: capability inertia, capability-signal energy, and the characteristic capability-propagation rate are operational quantities of the proposed artificial-intelligence framework. Whether artificial intelligence systems possess independently measurable quantities satisfying this relation is ultimately an experimental question.