Peers often publish parts of this stack, but not usually the full integrated framework. Knowing which pieces are common and which are emerging shows where this model adds the most.
What is common, and what is still emerging
Most institutions publish guidance and tool catalogs. Fewer connect those public artifacts to internal profiles, system cards, and publication controls.
Common at peer institutions
AI principles and high-level governance guidance
Acceptable use and academic integrity guidance
AI tool catalogs and comparison pages, including Microsoft and Google suite guidance
Vendor model-card links or vendor documentation for major suite providers and model vendors
Less common or emerging
Formal AI RMF profiles by domain
Reusable service-card templates with governance fields
System cards for university-run AI deployments
Unified visibility rules across all AI artifacts
What this means
The gap between common and emerging is exactly where this framework does its work.
Not speculative. The framework is built from documentation patterns that already exist in pieces across higher education, then assembled into a more complete institutional model — so adopting it is more about connecting existing practice than inventing new artifacts.