Not all Policies established as Machine-Readable Governance apply in the same way to every AI System. AI Governance includes Baseline Governance that applies broadly regardless of specific Use Context, as well as Governance whose Applicability depends on Context such as Jurisdiction, Domain, User / Subject, Purpose / Activity, and Risk / Impact.

For Narrow AI with relatively limited Functions and Use Scope, the anticipated Context is more constrained, allowing the required Governance Set to be defined with greater stability. Broadly applicable Requirements can be maintained as a Baseline Governance Set, while Applicable Requirements can be identified according to the limited Operational Context.

By contrast, more General AI may be used across different Jurisdictions, Domains, Users, Purposes, and Risk Levels. A single fixed Governance Set is therefore insufficient to determine which Governance actually applies in a particular use.

In such cases, Requirements that apply broadly without depending on specific Context are first maintained as the Baseline Governance Set. At the time of use, the relevant Context is then referenced to identify the Requirements within Machine-Readable Governance that apply to that particular situation.

The resulting set is the Applicable Governance Set. This does not modify Baseline Governance according to Context. Rather, it identifies, from Governance Sources that already possess Authority, the Requirements applicable within a specific Context. Accordingly, while Applicability may change with Context, the underlying Governance Requirements and their Authority are not rewritten.

As AI Capability increases and the range of possible Contexts expands, a Governance Structure is required that can associate increasingly diverse Governance Requirements with the appropriate Context and determine their Applicability.

The key relationship is therefore:

Increasing AI Capability requires increasing Governance Applicability Capacity.

This does not mean that more advanced AI should uniformly be subject to stricter Governance. Rather, as AI becomes more General and the range of possible Contexts expands, greater Capacity is required to correctly determine which Governance applies, in which Context, and under which Authority.