In our previous article, we argued that governance is the prerequisite for scalable AI systems. As organizations move from experimentation to deploying autonomous agents, governance can no longer rely on human oversight alone. Policies, controls, and access rules must be interpretable by machines. For this to work, AI systems require institutional traceability: the ability to understand where information originated, how it was transformed, and what policies govern its use. Metadata is the layer that makes those controls executable. In order for AI agents to operate safely and reliably, metadata must evolve from human-oriented documentation into machine-readable infrastructure that encodes provenance,…