This preprint develops a structural theory of AI governance centered on the concept of "decision without deciders." Rather than treating AI accountability as a problem of regulatory design, policy implementation, or institutional responsibility, the paper analyzes how accountability itself is being infrastructuralized across contemporary socio-technical systems. It argues that responsibility is no longer located in identifiable human actors, institutions, or decision-makers, but is increasingly embedded in distributed architectures of automation, prediction, and delegation. The paper constructs a conceptual framework for understanding AI governance as a transformation of accountability structures, not as a governance failure, but as a systemic reconfiguration of decision-making itself. --- Full text (HTML): https://hirokitamba-ops.github.io/paper1.html --- Part of the TLIM Research Program (Tri-Layer Integrated Model).For foundational definition see:https://doi.org/10.5281/zenodo.18667835 Version v2: Added references for indexing and citation network integration.