# Writing a University AI Policy Accreditors Will Accept: SACSCOC, MSCHE, WSCUC and NIST AI RMF

> Higher Education · ibl.ai
> Source: https://ibl.ai/courses/higher-education/university-ai-policy-and-accreditation
> Last updated: 2026-11-14

*SACSCOC, MSCHE, WSCUC and NIST AI RMF*

**A higher education course from ibl.ai (self-paced, 12 to 14 hours, free).** Write a university AI policy accreditors will accept: SACSCOC, MSCHE and WSCUC expectations, a NIST AI RMF committee charter and shared governance.

- **Price:** Free
- **Format:** Self-paced, online
- **Time:** 12 to 14 hours
- **Pace:** 3 hours per week
- **Level:** Intermediate
- **Language:** English
- **Subject:** Governance

[Enroll](https://lms.ibl.ai/platform/highereducation/courses/course-v1:highereducation+university-ai-policy-and-accreditation+self-paced)

## Course description

A university AI policy has to satisfy two readers at once: the campus community that will live under it and the accreditor that will ask for evidence it is followed. Most institutions have neither reader covered. In the EDUCAUSE 2025 AI Landscape Study, AI acceptable-use policies rose from 23 percent to 39 percent of institutions, yet only 9 percent said their cybersecurity and privacy policies were adequate for AI risk, and the AAUP's 2025 report found that 90 percent of members see institutional AI initiatives that have not become clear policies. This course teaches how to write a policy that holds up. You will read what SACSCOC, MSCHE, WSCUC and C-RAC have actually published, with dates and status, and what NECHE, HLC and NWCCU have not yet finalized. You will fold AI into the data-governance and information-security policies you already have, charter a governance committee on NIST AI RMF's four functions, set the attestation workflow for AI-assisted accreditation reports, and run a shared-governance process the faculty will recognize as theirs.

### About this course

A university AI policy has to satisfy two readers at once: the campus community that will live under it and the accreditor that will ask for evidence it is followed. Most institutions have neither reader covered. In the EDUCAUSE 2025 AI Landscape Study, AI acceptable-use policies rose from 23 percent to 39 percent of institutions, yet only 9 percent said their cybersecurity and privacy policies were adequate for AI risk, and the AAUP's 2025 report found that 90 percent of members see institutional AI initiatives that have not become clear policies. This course teaches how to write a policy that holds up. You will read what SACSCOC, MSCHE, WSCUC and C-RAC have actually published, with dates and status, and what NECHE, HLC and NWCCU have not yet finalized. You will fold AI into the data-governance and information-security policies you already have, charter a governance committee on NIST AI RMF's four functions, set the attestation workflow for AI-assisted accreditation reports, and run a shared-governance process the faculty will recognize as theirs.

### What you will be able to do

- State, with the document title, date and status, what each regional accreditor has published on AI, and distinguish a guideline from a policy, a joint statement and a proposed rule.
- Crosswalk a draft institutional AI policy to the SACSCOC guideline, the MSCHE policy and the WSCUC policy and identify every expectation the draft does not meet.
- Amend existing data-governance, information-security, procurement and academic-integrity policies with AI clauses rather than writing a stand-alone AI policy, and show where each clause came from.
- Draft an AI governance committee charter organized around NIST AI RMF's GOVERN, MAP, MEASURE and MANAGE functions, with a risk register seeded from NIST AI 600-1.
- Design an attestation and disclosure workflow for accreditation documents drafted with AI assistance that meets SACSCOC's and MSCHE's accuracy expectations.
- Run a shared-governance adoption process and a maintenance schedule that keeps the policy current as accreditor and federal positions change.

### Who this course is for

**Roles:** provosts and vice provosts, accreditation liaison officers and self-study chairs, CIOs and chief information security officers, general counsel and compliance officers, faculty senate and shared-governance leaders, and institutional research directors who assemble accreditation evidence.

**Institutions:** any institution accredited by SACSCOC, MSCHE, WSCUC, NECHE, HLC or NWCCU, including community colleges, regional publics, private nonprofits and system offices drafting a policy several campuses will adopt.

**Before you start:** familiarity with your institution's policy-approval process and with the standards of your accreditor. No technical background is required. The lab uses an AI agent through a browser on a supplied sample policy set.

### Format

- Estimated time: 12 to 14 hours.
- Level: intermediate. Assumes you have drafted or approved an institutional policy; assumes nothing about AI.
- Hands-on: one lab on a supplied sample policy set (six fictional policies for a fictional regional university), six templates you keep, two discussions, and a capstone on your own institution's policies.
- Structure: 4 sections, each ending in an AI conversation assessment, then a capstone assessment.

Self-paced. Every lesson is taught by an AI tutor that opens with a short story and works through one idea and one question at a time. Each section ends with an AI conversation assessment, and the course closes with a capstone assessment. Section assessments count for 60% and the capstone for 40%; 70% passes. There are no multiple-choice quizzes.

### Currency of this course

Last verified 2026-09-28. This is a regulatory course and the rules are still moving. As of this date: SACSCOC's guideline on AI in accreditation was endorsed by its Board of Trustees in December 2024; MSCHE's policy has been in force since 2025-07-01; WSCUC's policy was published 2024-11-19 and last modified 2025-09-30; C-RAC's joint statement is dated 2025-10-05; NECHE's AI policy is proposed, its comment period closed 2026-09-11 and final adoption is not confirmed; the course has not verified a formal AI policy from HLC or NWCCU. The U.S. Department of Education's supplemental priority on AI in education has been in effect since 2026-05-13. Every unit that states a rule cites the document it comes from. Re-check each accreditor's site before relying on anything here.

## Outline

### Section 0 · Start here

- 0.1 Orientation

### Section 1 · What accreditors have actually said

- 1.1 The landscape, with dates
- 1.2 SACSCOC
- 1.3 MSCHE, WSCUC, C-RAC and the accreditors still deciding
- 1.4 Section 1 assessment

### Section 2 · The federal frame and the risk framework

- 2.1 What Washington has and has not required
- 2.2 Scope: what this policy hands to other policies
- 2.3 Section 2 assessment

### Section 3 · Writing the policy

- 3.1 Fold, do not bolt on
- 3.2 The governance committee charter
- 3.3 Procurement, vendors and the lab
- 3.4 Section 3 assessment

### Section 4 · Attestation, adoption and keeping the policy current

- 4.1 AI in the self-study
- 4.2 Adoption and maintenance
- 4.3 Section 4 assessment

### Section 5 · Capstone & wrap-up

- 5.1 Capstone
- 5.2 Capstone assessment
- 5.3 Wrap-up

## Instructors

- ibl.ai Higher Education, Course team (ibl.ai)

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