All templates

University AI rules by institution, course, and assignment

A university policy sets institution-wide boundaries for data, approved tools, integrity, accessibility, research, employment, and accountability while defining academic authority. Administrators, academic integrity teams, faculty, students, research offices, libraries, IT, privacy, and disability services have different responsibilities.

Updated:

Sample university policy

The university permits responsible AI use for authorized teaching, learning, research, and administration subject to law, contracts, research protocols, professional duties, and institutional policy. Approval of a tool does not authorize every input or use.

Institutional rules govern security, privacy, records, research integrity, accessibility, procurement, and prohibited conduct. Instructors may set course and assignment rules within their authority, including stricter limits needed to assess a learning outcome. Requirements must be communicated before the relevant work and should explain permitted assistance and disclosure.

Students and staff remain accountable for submitted or relied-upon work. They must verify claims and sources, avoid fabricated citations, respect confidentiality and rights, and provide an accurate declaration where required. Researchers must additionally follow ethics approval, funder, publication, authorship, data-management, export, and disciplinary requirements.

Concerns about student work receive contextual human review under the institution’s established process. Detection output is not sole proof of authorship or misconduct and must not automatically determine a finding or penalty.

How the rule hierarchy works

Institutional policy establishes non-negotiable boundaries such as data protection and fair process. A course policy establishes the normal teaching approach. An assignment rule then identifies what the particular task is intended to assess. The university should say which rule controls and prevent retroactive changes.

  • Institution: approved tools, protected data, research and employment duties, accessibility, records, reporting, and due process.
  • Course: default approach, learning rationale, disclosure method, support, and consequences under existing procedure.
  • Assignment: exact allowed activities, prohibited assistance, evidence or process notes, and any deviation from the course default.
  • Conflict example: an assignment may prohibit AI drafting even when the course normally allows it, but it cannot authorize uploading restricted research or student data.

Example university matrix

These examples distinguish learning, research, and administration rather than applying one academic-integrity rule to all university activity.

  • Student asks for practice questions — Conditional; allowed by course rule, no live assessment content, student verifies answers.
  • Student submits generated literature analysis — Permission depends on the assignment; disclose allowed support and preserve assessed authorship.
  • Researcher summarizes de-identified public papers — Conditional; verify sources and follow research and publication requirements.
  • Researcher uploads identifiable participant transcripts — Approval required; ethics, consent, privacy, security, and tool terms must cover the use.
  • Administrator drafts a routine agenda — Allowed in an approved tool with authorized data and human review.

Write your policy

Customize this template

Decisions for university leaders

Define faculty authority, minimum syllabus notice, student appeal and support, detector governance, accessibility, research boundaries, records, and the process for approving tools. Clarify whether disclosure is always required, required for substantive help, or set by an identified assignment rule.

Use the university preset in the generator, and adapt Syllabus AI Policy for individual courses. This template is not legal advice or an expert-reviewed academic policy.

Example wording

Research disclosure

I used an approved AI tool to compare alternative headings and identify passages needing clarification. I did not provide restricted research data. The authors evaluated every suggestion and remain responsible for the article.

Sample policy

Example University Academic AI Use Policy

The names are placeholders. Review the rules and fill in the missing details before using this policy.

Read the sample policy
Audience
University or college
Scope
organization
Owner
To be designated
Status
Draft
Version
0.1
Effective date
To be confirmed
Review date
To be scheduled

Summary

  • University or college policy. Status: Draft. Version: 0.1.
  • Activity permissions: Allowed: 2; Allowed with conditions: 4; Approval required: 3; Prohibited: 1.
  • This draft approves no tools. Designate approved tools before use.
  • Secrets are never permitted in general-purpose AI tools; sensitive data requires exact data-type, tool, and use approval.
  • Suspected misuse requires fair human review; detection alone cannot establish misconduct or trigger a penalty.

1. Document control and scope

This policy applies across Example University to people and work covered by its authority. Owner: designated policy owner. Status: Draft. Version: 0.1. Region, if supplied, is review context only and does not establish local legal compliance.

2. Purpose and approach

This policy sets the rules for AI use and assigns accountability. Use is permission-based. AI may be used only for activities permitted in the activity matrix and subject to every listed condition.

3. Definitions

“AI tool” means software that generates, transforms, ranks, or analyzes content using an AI model. Assistive editing corrects or suggests presentation without supplying the learner's ideas or reasoning. Substantive generation creates or materially rewrites an answer, analysis, code, or other assessed content. “Approved tool” means a tool designated for a particular use and data type through the applicable approval process; familiarity or public availability is not approval.

4. Roles and responsibilities

The designated policy owner maintains this policy and coordinates its review. the designated approver decides requests to approve tools, exceptions, and uses within their authority. the person responsible for the work checks outputs before anyone relies on or releases them. Institutional leaders set defaults; instructors communicate course and assignment rules within their authority; learners remain responsible for submitted work.

5. Approved tools and approval process

No tools are currently designated as approved. Before use, the designated approver must approve the tool, intended activity, account or deployment, and data types involved. Public availability or prior use does not constitute approval.

6. Permitted-use matrix

The activity matrix is part of this policy. For each activity, its permission, conditions, and clarification apply. All listed conditions must be met.

Activity permissions and required conditions
ActivityPermissionConditions and clarification
BrainstormingAllowedNo activity-specific conditions. The policy's data and human-review safeguards still apply.
Grammar and spelling supportAllowedNo activity-specific conditions. The policy's data and human-review safeguards still apply.
TranslationAllowed with conditions
  • Use only an approved tool
  • Disclose the AI assistance
  • Verify facts, quotations, citations, and sources
TutoringAllowed with conditions
  • Use only an approved tool
  • Disclose the AI assistance
  • Verify facts, quotations, citations, and sources
Research assistanceAllowed with conditions
  • Use only an approved tool
  • Disclose the AI assistance
  • Verify facts, quotations, citations, and sources
CodingAllowed with conditions
  • Use only an approved tool
  • Disclose the AI assistance
  • Verify facts, quotations, citations, and sources
DraftingApproval required
  • Obtain written approval before use
  • A person must review the output before use
Substantive rewritingApproval required
  • Obtain written approval before use
  • A person must review the output before use
Graded workApproval required
  • Obtain written approval before use
  • A person must review the output before use
ExaminationsProhibitedNo activity-specific conditions. The policy's data and human-review safeguards still apply.

7. Prohibited uses

The matrix prohibits: Examinations. Do not submit generated work as independent work, fabricate sources or evidence, impersonate another person, or use AI contrary to the applicable assessment instructions. Do not use AI where law, contract, professional duty, or a controlling organizational rule prohibits it.

8. Data, privacy, confidentiality, and intellectual property

The only data categories selected for possible use are: public. Selecting a category does not by itself permit its use. Data may be entered only when the specific tool and proposed use are approved for that data type. Do not enter confidential information, personal data, student data, customer data, or other sensitive data unless the tool and proposed use have been expressly approved for that exact data type. Credentials, passwords, access tokens, private keys, authentication codes, and other secrets must never be entered into general-purpose AI tools. Inputs and outputs remain subject to access, retention, intellectual-property, contractual, and confidentiality requirements. If unsure, stop and ask the policy owner.

9. Output verification and human accountability

A person remains accountable for AI-assisted work. Before using or releasing it, check factual accuracy, calculations, citations, originality, bias, security, rights, and suitability for the intended audience. AI output is neither an authority nor a verified source. Decisions affecting grades, discipline, admission, accommodations, or access require accountable human review and the institution's authorized process.

10. Disclosure and attribution

Disclose AI assistance when it creates, materially rewrites, analyzes, or otherwise makes a substantive contribution. A declaration must accurately describe the use. The following example is not a declaration on the user's behalf. A suitable declaration might read: “I used an AI tool to develop initial questions and organize ideas. I wrote the submitted text and verified the sources myself.”

11. Learning, assessment, and course rules

Institutional rules are the default. Course and assignment instructions may add detail but do not override institutional prohibitions. Research use must follow applicable research, ethics, privacy, sponsor, publication, and records processes. Assessed work must reflect the learning being evaluated, with accessible explanation of permitted assistance and disclosure.

12. Review, reporting, and exceptions

Report concerns to the designated policy owner through the usual organizational channel. Report suspected data exposure, unsafe output, rights concerns, or material misuse promptly. A person must consider context, discuss the concern with the student, and follow the institution's existing review and appeal process. An AI-detection result may inform review but must never be the sole evidence of misconduct or automatically trigger a grade penalty or discipline. Exceptions must be written, limited in scope and duration, approved by the designated approver, and retained by the policy owner.

13. Training, communication, and acknowledgment

Before covered users begin AI use, the policy owner will provide onboarding on the matrix, approved tools, data limits, disclosure, verification, and reporting. Covered users will be asked to acknowledge that they received and understood the policy; acknowledgment does not waive rights or replace training.

14. Review and version history

The policy owner will review this policy annually and after a material incident, tool change, or change in applicable obligations. Changes require the designated approval process and notice to affected people. Confirm the effective date before adoption. Schedule the next review date. Version history: Version 0.1 | Status: Draft | Change: Initial draft.

Decisions to confirm

  • Name the policy owner.
  • Name the role or person authorized to approve tools and exceptions.
  • Designate tools, deployments, intended uses, and approved data types.
  • Set an effective date before adoption.
  • Schedule the next review date.

Implementation checklist

  • ☐ Confirm and name the policy owner.
  • ☐ Review the sensitive-data rules for each proposed data type and use.
  • ☐ Designate approved tools before permitting AI use.
  • ☐ Resolve 5 open decisions before adoption.
  • ☐ Complete the authorized approval process; this document remains Draft.
  • ☐ Communicate the matrix, safeguards, disclosure rules, and reporting route.
  • ☐ Schedule the annually review.

Acknowledgment

I received the Example University Academic AI Use Policy and had an opportunity to ask questions. I understand where to find the current activity matrix and how to report concerns. This acknowledgment does not replace training or waive any rights. Name: ____________________ Signature: ____________________ Date: ____________________

This policy draft is not legal advice. Have the appropriate people review it before adoption.

Frequently asked questions

Should one university rule apply to every assignment?

Institutional boundaries should be consistent, but allowed assistance can differ with learning outcomes. Require timely, accessible assignment instructions and explain the hierarchy.

How should AI use be disclosed?

Ask for the tool, purpose, material assistance, and the student’s verification where those details are relevant. A declaration must describe actual use; it should not be inserted automatically.

Does editing with AI always count as misconduct?

No. The answer depends on the communicated rule and assessed skill. Grammar support might be allowed while substantive rewriting is not, so define the boundary with examples.

How should suspected violations be reviewed?

Consider instructions, work and process evidence, context, accessibility, and the person’s explanation under established procedures. Do not let a detector score automatically establish a finding or penalty.

Sources and references

These drafts have not been reviewed by a lawyer or subject-matter expert. Have your legal or policy team review them before use. They are not legal advice or proof of compliance.

NIST AI Risk Management Framework

NIST describes its AI Risk Management Framework as voluntary guidance for managing AI-related risks and incorporating trustworthiness into AI use.

Use it as a review reference when assigning owners and considering risks, safeguards, and ongoing oversight. This generator does not perform a NIST assessment.

UNESCO: Guidance for generative AI in education and research

UNESCO’s guidance emphasizes a human-centred approach, data privacy, and age-appropriate use of generative AI in education and research.

For school, university, and classroom policies, review student data, age restrictions, access, and the learning purpose of each permitted activity with the appropriate institutional owners.

Pangram: Useful AI policies for educators

Pangram’s classroom-policy article compares blanket restrictions with a tier-based approach that allows different levels of AI assistance for different assignments.

Use the examples to discuss classroom boundaries, then choose your own permissions in the generator. These approaches are options, not a requirement to adopt a particular rule.

Pangram for universities

Public reference selected for the university ai rules by institution, course, and assignment page.

Read the original source in its own context. It does not replace qualified local review or establish that this draft is compliant.

Pangram guidance for educators

Public reference selected for the university ai rules by institution, course, and assignment page.

Read the original source in its own context. It does not replace qualified local review or establish that this draft is compliant.

ISO/IEC 42001 — AI management systems

Public reference selected for the university ai rules by institution, course, and assignment page.

Read the original source in its own context. It does not replace qualified local review or establish that this draft is compliant.

References do not imply endorsement.

Create your AI policy