Who it's for

One framework, many roles

Campus AI is a team sport, no single office owns it. Pick the role that fits you for a curated path through the framework: an honest frame, a few first steps, and the destinations that matter most to you.

For Faculty, senate, teaching & learning centers

Faculty & academic governance

Set classroom and academic-integrity expectations, and shape the rules.

Your concern is teaching, learning, academic integrity, and academic freedom, and a fair say in decisions that affect them. The framework is built to work with shared governance, not around it. Start with the policy and principles pillars, where faculty voice carries the most weight.

Shared governance: who decides what

AI doesn't change the lines of academic authority, and this framework is built to map onto them rather than override them. It informs the faculty's deliberation, it does not replace it.

Faculty-led

Faculty hold primary authority

The academic core. These belong to the faculty through shared governance, the framework informs them, it does not decide them.

Curriculum & program design
Instructional methods & AI use in the classroom
Assessment design & academic-integrity standards
Scholarly & research use of AI

Shared

Decided together, through governance

Co-designed by faculty, administration, and students, then ratified through the bodies that already hold legitimacy.

Institution-wide AI principles & values
Campus AI policy & acceptable use
Risk tiers & proportionate review
Program-level student AI-literacy outcomes

Administrative

Operational & stewardship roles

Where administration and IT carry the weight, in service of the academic mission, not in place of it.

Tool procurement, contracts & vendor management
Data classification & security controls
System documentation & the registry
Infrastructure & enterprise integration

Why higher education governs AI differently

Most AI-governance advice is written for corporations. Higher education is not a company, and governing AI well means starting from what makes the academy distinct.

In a companyOn a campus

One bottom line to optimize.

A dual mission, teaching and research, each carrying its own distinct AI questions.

AI autonomy is mainly a risk to manage.

Academic freedom is a value to protect: autonomy in teaching and inquiry is foundational, not an exception.

A single executive chain of command.

Distributed authority, senates, colleges, and departments each govern within their own sphere.

Users and customers to serve.

Students are rights-holders, owed FERPA protection, due process, and an educational duty of care.

Policy issued top-down on a sprint cadence.

Policy ratified through faculty bodies on the rhythm of the academic calendar.

Growth and profit define success.

A public mission, access, equity, and the public good, defines what “good AI” even means.

Your path

1
See where your authority sits
A map of who decides what, and why higher education governs AI differently than a company.
Shared governance
2
Set course expectations
Ready-to-adapt syllabus AI statements and a red/yellow/green acceptable-use grid by audience.
Policies & Guidelines
3
Shape the principles
How institution-specific AI values get made, and where faculty co-design belongs.
AI Principles
4
See it in teaching
Real teaching-and-learning AI use cases, shown with their risks and the path each follows.
Use cases
5
Find your voice in governance
Where shared governance and faculty engagement fit the operating model.
Engagement & Collaboration

Where to start: adapt one syllabus statement and bring it to your next department meeting.

Go-to destinations

Policies & Guidelines AI Principles Use cases