Accountability Boundaries in AI Agentic Ecosystems

A new theory from arXiv (2605.23179) examines how accountability boundaries persist in agentic AI ecosystems even when technical interfaces become modular. The paper introduces "accountability assets"—complementary resources that make AI outputs legitimate, auditable, and assignable to a responsible party. It argues that verification cost and responsibility transferability determine whether execution and accountability boundaries can move together. Three boundary strategies are identified: component, integrated, and dual-track. The concept of "rule debt" is also introduced. This theoretical framework addresses the challenge of maintaining accountability in increasingly modular and disaggregated AI systems.