Scope should reflect where AI use genuinely needs to be governed. That may include specific products, services, workflows, teams, vendors, internal use cases, or decision-related activities. If scope is too broad, implementation becomes heavier than necessary. If it is too narrow, governance may not match operational reality. Good scoping requires a realistic view of how AI is actually developed, procured, deployed, monitored, and used.