Semantic Flow is a structural design theory that describes how structural conditions, including meaning state, shape the emergence, persistence, and dissipation of behavior within complex systems. Unlike management frameworks that prescribe solutions or optimize performance, Semantic Flow identifies the conditions under which systems inevitably lose momentum. The theory models systems as energy conversion processes, where effective action is determined by meaning permeability, structural loss, and temporal delay. This paper presents the foundational concepts, the Flow Law, six structural breakdown patterns derived as necessary consequences of the theory's equations, and the implications for an era in which AI systems amplify energy input without altering structural conditions. Keywords: behavioral systems theory, structural conditions, meaning state, structural loss, temporal delay, structural breakdown patterns, energy conversion, organizational dynamics, AI systems