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 1Agentic 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.1Author(s), Agentic AI and the Next Intelligence Explosion, arXiv preprint, 2026. Avail-able: https://arxiv.org/abs/2603.20639