From Agents to Structure : Defining the Boundary of Intelligence in AI Systems

Recent work on agentic AI has framed intelligence as the coordinated activity of decision-making agents operating through interaction, delegation, and distributed problem solving [1]Agentic AI and the Next Intelligence Explosion. That formulation captures an important domain of AI behaviour,but it leaves open a structural question that becomes unavoidable under scale: at whatpoint does intelligence cease to be meaningfully attributable to identifiable agents andbecome a property of the larger system they compose? This paper addresses that question by defining the boundary between agent-based and structural intelligence in AIsystems. The analysis argues that agent-based intelligence remains valid where decision units are local, interaction is traceable, and causal attribution remains bounded, while structural intelligence emerges where large-scale coordination, persistent dependency, and non-local allocation make the system itself the operative locus of intelligence. The contribution of this paper is not a new theory of AI, but a boundary definition that specifies the range within which agentic models remain valid and the conditions under which intelligence must be treated as structural.[1]Author(s), Agentic AI and the Next Intelligence Explosion, arXiv preprint, 2026. Avail-able: https://arxiv.org/abs/2603.20639