AI Principles

Turn borrowed values into institution-specific principles that actually decide cases.

Principles are the values layer of the framework: the small set of commitments (fairness, transparency, accountability, human oversight, and privacy) that downstream decisions are intended to honor. The test of a principle is whether it can decide a real case.

The eight pillars

• 1. Campus Mission & Vision
• 2. AI Principles
• 3. AI Policies & Guidelines
• 4. Governance, Risk, Compliance & Data Governance
• 5. AI Engagement & Collaboration
• 6. Campus Readiness
• 7. Roles & Responsibilities
• 8. Implementation & Operations

Tools & guides

• Find Your Starting PointA short maturity triage that places your campus in one of three tiers.
• The First 90 DaysA stage-aware AI governance action plan. Pick where your institution actually stands and get a 90-day arc sized to it.
• AI Maturity AssessmentAssess institutional AI maturity across the eight pillars.
• AI Strategic CompassScore and prioritize candidate AI initiatives on five categories and map each to a proportionate-review band.
• AI Tool Evaluation MatrixMatch any AI tool to the data it may touch. Classify the data.
• AI Governance Question GuideA structured diagnostic across the Nine AI Governance Domains for higher education.
• How AI Enters CampusThe six pathways AI arrives on campus.
• Standards AlignmentHow the Campus AI Framework maps to NIST AI RMF.