If governance through I2EA were confined to a single AI system, company, or country, each could use its own tagging system. In the real AI ecosystem, however, information and processes move across multiple AI systems, organizations, industries, countries, and regions. To make governance information interoperable across these boundaries, a commonly understandable tag structure is required.

Consider information generated by an AI system within one company, processed by an AI Agent provided by another AI Provider, and subsequently used by an organization in another country. If each participant records Fact, Evaluation, Policy, and Process in different formats, the receiving system cannot directly interpret what that information means. Translation or reassessment may be required, creating the risk that information is lost or its meaning altered.

Umecohming represents such governance information through a common structure. Importantly, this does not require every organization or country to adopt the same Policies or value judgments. What is standardized is not the substance of the decision, but the structure through which governance information is described, identified, and exchanged.

This also reflects the principle introduced in II-1.2 that “tags do not make decisions.” Even when the same tags are received, the final Decision may differ depending on Japanese law, EU regulation, internal organizational Policies, professional rules, or other applicable frameworks. Common tags are not intended to eliminate these differences. Rather, they enable different governance actors to reference the same information while making decisions according to their respective Authorities and Policies.

Nor does every system need to use every tag. The tags required will vary according to the information and purpose involved, and new attributes or evaluation criteria may emerge over time. What should therefore be standardized is not a fixed number or set of tags, but a common structure through which tags can be identified, classified, exchanged, and interpreted by machines.

With this common structure, governance information can accompany information as it moves among different AI Providers, companies, governments, organizations, and individuals. Governance information accumulated in previous processes therefore does not need to be discarded and reconstructed from zero each time information crosses a system or organizational boundary.

Accordingly, the Unified Tag Structure is not a mechanism for standardizing rules around the world. Rather, it provides a common language through which actors operating under different rules can understand, exchange, and reuse governance information.

Through this common structure, I2EA extends governance beyond individual AI systems into interoperable governance that can operate across organizational, industrial, and national boundaries.