What is this course about?
Most campus AI policies are memos that age badly. This course builds policy as a governance system: who owns it, which four policies you actually need, how each maps to a recognized framework, and what review cadence keeps it from calcifying. It treats the faculty academic freedom conflict as real rather than something to be drafted around.
Who is this course for?
- Provosts and vice provosts
- General counsel and compliance officers
- Faculty senate leadership
- CIOs and accreditation liaison officers
What do I need before starting?
- Access to your institution's existing academic integrity and IT policies
- No technical background required
What will I be able to do afterwards?
- Assign clear ownership for AI policy across cabinet, senate, and IT
- Draft the four distinct policies an institution needs rather than one blanket statement
- Map policy clauses to NIST AI RMF functions so it reads as a framework
- Identify accreditation exposure created by AI in academics and student services
- Negotiate the academic freedom conflict explicitly rather than avoiding it
What does each module cover?
Who should own AI policy on a campus?
40 minGovernance structure first — the ownership question determines whether the policy is enforceable.
Objectives
- Map decision rights across cabinet, senate, IT, and compliance
- Choose between a standing committee and distributed ownership
- Establish an escalation path for contested decisions
Topics
Activity. Draw your institution's AI decision-rights map and identify the contested cells.
Which four policies do you actually need?
45 minAcademic use, staff use, procurement, and data — separated because they have different owners and different risks.
Objectives
- Distinguish the four policy domains and their owners
- Identify what belongs in each and what does not
- Avoid the single-blanket-policy failure mode
Topics
Activity. Sort thirty real policy statements into the four domains and find the ones that belong nowhere.
How do you map policy to the NIST AI RMF?
50 minTurning a policy document into something that reads as a recognized framework to an auditor.
Objectives
- Map policy clauses to Govern, Map, Measure, and Manage functions
- Identify the functions your draft policy leaves empty
- Produce a crosswalk an auditor can follow
Topics
Activity. Build the crosswalk for your draft policy and mark every empty function.
What is your accreditation exposure?
45 minWhere AI touches substantive change, academic integrity, and student services in a way an accreditor will ask about.
Objectives
- Identify AI uses that could constitute substantive change
- Anticipate accreditor questions about academic integrity
- Prepare the student services and disclosure narrative
Topics
Activity. Draft the answers to five likely accreditor questions about AI at your institution.
How do you handle the academic freedom conflict?
50 minThe genuine tension between faculty autonomy over pedagogy and institutional risk management.
Objectives
- State the conflict accurately rather than minimizing it
- Identify what the institution may legitimately mandate
- Design consultation that produces agreement rather than resentment
Topics
Activity. Negotiate a contested clause in a role-play with faculty senate and administration roles.
What procurement clauses protect the institution?
45 minThe contract terms that determine whether you keep control of your data and your options.
Objectives
- Specify required clauses on model training rights and data residency
- Require portability and exit terms
- Build the evaluation rubric procurement will actually use
Topics
Activity. Write the required-clause list and test it against a real vendor agreement.
How do you keep the policy from calcifying?
40 minReview cadence, sunset clauses, and the amendment path that lets policy track a fast-moving field.
Objectives
- Set a review cadence tied to a real trigger
- Write sunset clauses for time-sensitive provisions
- Design an amendment path that does not require a full senate cycle
Topics
Activity. Write the review and amendment provisions for your policy.
Assembling the policy skeleton
55 minThe workshop module: a complete policy skeleton with the NIST crosswalk attached.
Objectives
- Assemble a policy skeleton across all four domains
- Attach the framework crosswalk
- Plan the consultation and approval sequence
Topics
Activity. Assemble the skeleton and present the approval path to the cohort.
What is the capstone project?
Institutional AI policy skeleton with framework crosswalk
Produce a four-domain policy skeleton for your institution with clauses mapped to NIST AI RMF functions, an accreditation exposure assessment, procurement requirements, and a review and amendment plan.
Deliverable: A policy skeleton ready for institutional consultation, with the crosswalk attached.
How are learners assessed?
- Crosswalk completeness — every NIST function must be addressed or explicitly deferred
- Role-play negotiation assessed on whether agreement was reached without a fudge
- Capstone reviewed by a colleague in a different institutional role
What ships with the course?
Facilitator guide
Session-by-session running order, discussion prompts, and the questions that reliably derail a room.
Learner workbook
Exercises, checklists, and the templates each module's activity produces.
Hands-on lab environment
A sandboxed ibl.ai deployment so exercises run against real agents, not screenshots.
Assessment bank
Scenario questions and rubric criteria mapped to each stated learning outcome.
Source bibliography
Every primary regulation and standard cited on this page, linked and dated.
Which AI agents does this course use?
The hands-on modules run against agents already deployable on the ibl.ai platform for higher education.
Where does the course material come from?
Every module is grounded in primary sources — the regulation, standard, or research itself, not a summary of it. Each was resolved at authoring time.
- AI Risk Management Framework
NIST
The framework the policy crosswalk is built against in Module 3.
- NIST AI 600-1, Generative AI Profile
NIST
Generative-AI-specific risks the policy must name explicitly.
- ISO/IEC 42001, AI management systems
ISO
Alternative management-system framing for institutions pursuing certification.
- Student Privacy Policy Office
U.S. Department of Education
Constrains the data governance policy domain.
Delivery notes
Binding guidance for anyone preparing and delivering this course.
- Module 5 must be a real negotiation, not a lecture about balance. Assign genuine opposing positions and let the role-play fail if the participants cannot reach agreement — the failure is the lesson.
- Do not ship a fill-in-the-blank policy template. Institutions that adopt a template without the governance work end up with an unenforceable document, which is the failure this course exists to prevent.
- The accreditation module needs regional variation. Verify current substantive-change guidance for the accreditor relevant to each cohort rather than generalizing.
- Keep the ISO 42001 material proportionate — most institutions will not certify. Present it as an option with a stated cost, not a recommendation.
- This is a header-adjacent policy topic; have counsel review the full deck before external delivery.
Why run AI training on a platform you own?
You own the course, not a licence to it
Course content, learner data, and the platform run inside your perimeter — you own all the code and the data.
Model-agnostic delivery
Run the course's AI components on any LLM — Claude, GPT, Llama, Gemini, Command — and switch anytime.
No per-seat training licences
Usage-based or self-hosted, so cost tracks actual use rather than headcount.
Deploy anywhere
Cloud, private VPC, on-premise, or fully air-gapped — including for cohorts that cannot use public AI tools.
Frequently asked questions
What does the Writing a Campus AI Policy That Survives Accreditation course cover?
Most campus AI policies are memos that age badly. This course builds policy as a governance system: who owns it, which four policies you actually need, how each maps to a recognized framework, and what review cadence keeps it from calcifying. It treats the faculty academic freedom conflict as real rather than something to be drafted around. It runs 5.5 hours across 8 modules across 8 modules, at intermediate level, and closes with a capstone: Institutional AI policy skeleton with framework crosswalk.
Who should take Writing a Campus AI Policy That Survives Accreditation?
It is written for Provosts and vice provosts, General counsel and compliance officers, Faculty senate leadership, CIOs and accreditation liaison officers. Prerequisites: Access to your institution's existing academic integrity and IT policies; No technical background required.
Can we run this course on our own infrastructure?
Yes. ibl.ai is model-agnostic and deploy-anywhere — cloud, private VPC, on-premise, or fully air-gapped — and you own all the code and the data. Cohort data, submissions, and any material learners upload stay inside your perimeter, which matters for higher education teams that cannot send work to a public AI tool.
How do we get access to Writing a Campus AI Policy That Survives Accreditation?
Request access and we will set it up for your cohort — hosted by ibl.ai, or running against your own deployment. Tell us the group size and timing you need, and whether it should run inside your own perimeter.
How much does AI training for higher education cost on ibl.ai?
There is no per-seat pricing — you pay for usage or self-host and pay only for the infrastructure, so a 5,000-person rollout does not cost 5,000 licences. 1.6M+ users across 400+ organizations run the platform this way, including NVIDIA, MIT, and Syracuse University.