Manchester, United Kingdom Last checked Oct 21, 2026

The University of Manchester

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Can I use AI for my coursework?Senate 4-Category Framework Do I need to disclose AI use?Cite them Right Standards Can I upload sensitive data?Upload Restrictions & Recording Safe Harbor Which tools can I access?Copilot Chat (All) & M365 Copilot (Phased)

Use in ChatGPT ↗Before you submitAdvice and precautions Record updates ↓

Explore the current record by topic

Coursework & Assessment Categories

Senate 4-Category Framework

Under Senate Policy DocID 79331 §2.1.1, assessments are categorized into four levels (Category A: AI Prohibited, Category B: AI Minimal, Category C: AI Permitted, Category D: AI-Integrated) by Course Unit Directors and clearly stated in unit specifications and Canvas briefs (§2.1.3). Students may choose not to use AI for Categories A, B, and C without disadvantage, but this choice does not apply to Category D assessments which assess AI learning outcomes (§2.1.2). In Category A, all AI use including proofreading and text editing is prohibited; in Category B, AI is restricted to presentation only (fluency, grammar, spelling, formatting) without altering student ideas, arguments, or conclusions.

Official source ↗

Examinations & Timed Assessments

Assessment Categorization & Exam Rules

Examinations and timed assessments are categorized individually under the four-category framework (DocID 79331 §2.1.1). Under Academic Malpractice Procedure DocID 639 §3.1.2.5 and §4.3.1, students must adhere strictly to examination conditions communicated before the exam, and possessing or using unauthorized AI tools or online materials in examination sittings constitutes academic malpractice.

Official source ↗

Acknowledgment & Citation

Cite them Right Standards

Under University Library referencing guidance, students must cite generative AI tools when using text or images directly in their work following 'Cite them Right' conventions. Where asked or deemed appropriate, students should include an overview acknowledgement at the start of work or in a footnote. An appendix detailing relevant prompts, outputs, generation dates, and modification statements is required when referencing AI as personal communication or when instructed by School guidance. Using tools for basic grammar and spell checking does not require acknowledgement unless School guidance requires it.

Official source ↗

Data Protection & Copyright Restrictions

Upload Restrictions & Recording Safe Harbor

Under Senate Policy DocID 79331 §2.2.1(c), students must not upload University-owned copyright materials (such as lecture recordings, slides, handouts, or examination questions) to external commercial AI tools. Under §2.2.2, students are explicitly permitted to upload session recordings into University-provided Microsoft 365 Copilot for study support. Under §2.3.1, staff members who use AI in Teaching and Learning activities must adhere to the University's AI Guidelines, and only the University-provided Microsoft 365 Copilot service may be used for student-identifiable or confidential data.

Official source ↗

Approved AI Tools

Copilot Chat (All) & M365 Copilot (Phased)

The University provides Microsoft Copilot Chat with Commercial Data Protection to all active students and staff using University credentials. Microsoft 365 Copilot suite is deploying in phased license cohorts across 65,000 colleagues and students. NebulaONE is provided as an enterprise cloud AI development sandbox. Under DocID 79331 §2.1.1 and §2.2.1, having access to institutional AI tools does not confer permission to use them in Category A assessments.

Official source ↗

Research, Data Synthesis & Publication

Author Responsibility & Peer Review Confidentiality

Under StaffNet Research Guidelines, any use of AI to synthesise research data must be completely transparent, and fabricating or falsifying data with AI constitutes research misconduct. Corresponding authors carry ultimate responsibility for publication credibility and must declare significant AI assistance. Researchers reviewing papers or grants must preserve peer review confidentiality and never upload unpublished manuscripts into external AI services.

Official source ↗

More reviewed record topics

Malpractice Detection, Viva Voce & Case Handling

DocID 639 §4.2, §4.4 Viva Voce & §5 Case Routing

The University does not currently use software claiming to detect generative AI; Turnitin alone does not confirm malpractice and academic judgment is required. Under Academic Malpractice Procedure DocID 639 §4.4.2, where indicators raise concerns of commissioned work without direct evidence, or available information does not satisfy the balance of probabilities, a viva voce can be arranged in agreement with the School Officer to demonstrate authorship; it does not contribute to the mark. If held, it should not normally take place more than 30 working days after the assessment feedback deadline (§4.4.3.1); the student should receive at least five working days notice explaining its nature, purpose and potential outcomes (§4.4.3.2). Accompaniment by a person of the student’s choice is for support only without participation (§4.4.3.4), and reasonable adjustments must be made (§4.4.3.5). The viva itself cannot impose a penalty (§4.4.4.2); case handling follows the applicable AUO/SDP/UDP procedures (§5.1–5.5).

Official source ↗

Teaching Practice & Assessment Governance

Assessment Briefs, Group Work & Staff M365 Rule

Senate Policy DocID 79331 and Faculty guidance mandate that Course Unit Directors specify AI categories in unit specifications and Canvas briefs (§2.1.3), establish group work logging rules and require prior peer consent before recording group discussions (§2.1.4–2.1.5), and require teaching staff handling student-identifiable data to use M365 Copilot (§2.3.1). Faculty guidance (FSE, BMH) supplements central policy.

Official source ↗

Cloud Sandbox Governance & Data Security

Commercial Data Protection & NebulaONE Gateway

IT Services and Information Governance establish clear tenant boundaries for Copilot Chat, Microsoft 365 Copilot, and NebulaONE cloud sandbox, ensuring user authentication, commercial data encryption, and exclusion of university data from public LLM training.

Official source ↗

Do

Always verify the designated AI assessment category (A, B, C, or D) in the course unit handbook and Canvas assessment brief before starting coursework (DocID 79331 §2.1.1, §2.1.3).
Source guidance
Always verify the designated AI assessment category (A, B, C, or D) in the course unit handbook and Canvas assessment brief before starting coursework (DocID 79331 §2.1.1, §2.1.3).
Scope
Audience and activity scope varies strictly by source: Senate Policy DocID 79331 governs taught assessment categorization (Categories A–D) and copyright upload restrictions; Library referencing guidance governs citation and acknowledgement in coursework; Academic Malpractice Procedure DocID 639 governs malpractice investigations, detector prohibition, and authorship vivas; IT Services policies govern Copilot and NebulaONE tenant access.
Under Senate Policy DocID 79331 §2.1.1, all coursework assessments must be assigned to one of four AI categories (A: AI Prohibited, B: AI Minimal, C: AI Permitted, D: AI-Integrated); under §2.1.2 students may choose not to use AI in Categories A, B, and C (excluding Category D), and under §2.1.3 the category must be published in unit specifications and assessment briefs.
Original evidence and scope
Under Senate Policy DocID 79331 §2.1.1, all coursework assessments must be assigned to one of four AI categories (A: AI Prohibited, B: AI Minimal, C: AI Permitted, D: AI-Integrated); under §2.1.2 students may choose not to use AI in Categories A, B, and C (excluding Category D), and under §2.1.3 the category must be published in unit specifications and assessment briefs.
CL-008
Senate-approved four-tier assessment categorization framework across all course units
The University has produced a dedicated AI in Teaching and Learning Policy which sets out a shared framework for the use of AI in assessment at the University, defining clear and transparent expectations for students and staff when using AI across undergraduate and postgraduate teaching, learning, assessment, and research or dissertation activities.
Teaching and Learning > Assessment; Extracted text SHA256 6ca485f22cb29ccf5fe174cc9ee2437d2543ed93b82235be305e3df79d901fb9; original binding lines 75–75; characters 6291–6642; excerpt offset 0–351
Official university source ↗
a) AI Prohibited: AI is not permitted or is unable to be used in this assessment. The assessment information should include additional information such as examples or detail of what is not permitted, if it is likely to provide clarity for students.
Section 2.1.1(a), Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 136–138; characters 7925–8195; excerpt offset 0–270
Official university source ↗
b) AI Minimal: AI is permitted to be used in this assessment in limited ways that contribute to the presentation (for example surface level use to improve grammar, fluency, and formatting) without changing the ideas, arguments or conclusions developed by the student. The assessment information must set out what is acceptable AI use. Students who do not wish to personally use AI tools can undertake the assessment.
Section 2.1.1(b), Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 140–145; characters 8205–8676; excerpt offset 0–471
Official university source ↗
c) AI Permitted: AI may be used to complete the assessment. The assessment information must set out what is acceptable AI use. The assessment brief should explain how students who do not wish to personally use AI tools can undertake the assessment.
Section 2.1.1(c), Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 147–150; characters 8686–8975; excerpt offset 0–289
Official university source ↗
d) AI-Integrated: AI use is necessary to meet the course unit intended learning outcomes. This does not imply that all AI use is permitted. The assessment information must set out what is acceptable AI use and should explain why AI use is required to meet the intended learning outcomes.
Section 2.1.1(d), Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 152–155; characters 8985–9305; excerpt offset 0–320
Official university source ↗
2.1.2 Students may choose not to use AI for assessment, unless the assessment has been designated as Category D.
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Official university source ↗
2.1.3 Information relating to the category of AI use for the assessment must be clearly communicated to students and included in the assessment brief and unit specification.
Section 2.1.3, Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 161–163; characters 9432–9623; excerpt offset 0–191
Official university source ↗
Under Senate Policy DocID 79331 §2.1.1, using an AI tool to assist with grammar, fluency, or spelling is permitted in Category B (AI Minimal) assessments provided it does not alter student ideas, arguments, or conclusions, but AI proofreading is not permitted in Category A (AI Prohibited) assessments.
Original evidence and scope
Under Senate Policy DocID 79331 §2.1.1, using an AI tool to assist with grammar, fluency, or spelling is permitted in Category B (AI Minimal) assessments provided it does not alter student ideas, arguments, or conclusions, but AI proofreading is not permitted in Category A (AI Prohibited) assessments.
CL-009
Assessment-category bounds on proofreading: permitted in Category B for presentation only without altering ideas, strictly prohibited in Category A
a) AI Prohibited: AI is not permitted or is unable to be used in this assessment. The assessment information should include additional information such as examples or detail of what is not permitted, if it is likely to provide clarity for students.
Section 2.1.1(a), Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 136–138; characters 7925–8195; excerpt offset 0–270
Official university source ↗
b) AI Minimal: AI is permitted to be used in this assessment in limited ways that contribute to the presentation (for example surface level use to improve grammar, fluency, and formatting) without changing the ideas, arguments or conclusions developed by the student. The assessment information must set out what is acceptable AI use. Students who do not wish to personally use AI tools can undertake the assessment.
Section 2.1.1(b), Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 140–145; characters 8205–8676; excerpt offset 0–471
Official university source ↗
Using an AI tool to correct grammar or spelling is acceptable, but where a student uses an AI tool for proofreading work submitted for assessment, they should ensure that use of the tool does not result in substantive changes to the content or meaning of their work or go beyond what is allowed for the assessment.
Teaching and Learning > Proofreading; Extracted text SHA256 6ca485f22cb29ccf5fe174cc9ee2437d2543ed93b82235be305e3df79d901fb9; original binding lines 79–79; characters 7174–7488; excerpt offset 0–314
Official university source ↗
Under Senate Policy DocID 79331 §2.1.1(a), assessments designated as Category A (AI Prohibited) completely forbid using AI tools to assist in the preparation or writing of the submission, including for generating content or for proofreading / editing text, and the assessment brief must explain why this prohibition is in place.
Original evidence and scope
Under Senate Policy DocID 79331 §2.1.1(a), assessments designated as Category A (AI Prohibited) completely forbid using AI tools to assist in the preparation or writing of the submission, including for generating content or for proofreading / editing text, and the assessment brief must explain why this prohibition is in place.
clm-man-cat-prohibited
Category A AI Prohibited definition and mandatory assessment brief details
a) AI Prohibited: AI is not permitted or is unable to be used in this assessment. The assessment information should include additional information such as examples or detail of what is not permitted, if it is likely to provide clarity for students.
Section 2.1.1(a), Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 136–138; characters 7925–8195; excerpt offset 0–270
Official university source ↗
Under Senate Policy DocID 79331 §2.1.1(b), assessments designated as Category B (AI Minimal) permit using AI tools only in relation to presentation—such as to improve fluency, grammar, or spelling, or to assist with formatting—and strictly forbid using AI tools to generate ideas, arguments, conclusions, or other substantive content.
Original evidence and scope
Under Senate Policy DocID 79331 §2.1.1(b), assessments designated as Category B (AI Minimal) permit using AI tools only in relation to presentation—such as to improve fluency, grammar, or spelling, or to assist with formatting—and strictly forbid using AI tools to generate ideas, arguments, conclusions, or other substantive content.
clm-man-cat-minimal
Category B AI Minimal definition and presentation-only boundary
b) AI Minimal: AI is permitted to be used in this assessment in limited ways that contribute to the presentation (for example surface level use to improve grammar, fluency, and formatting) without changing the ideas, arguments or conclusions developed by the student. The assessment information must set out what is acceptable AI use. Students who do not wish to personally use AI tools can undertake the assessment.
Section 2.1.1(b), Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 140–145; characters 8205–8676; excerpt offset 0–471
Official university source ↗
Under Senate Policy DocID 79331 §2.1.1(c), assessments designated as Category C (AI Permitted) allow students to use AI tools for wider tasks, but require assessment briefs to state which tools and outputs are allowed, mandate that submitted text must be authentic student work, and require that a non-AI pathway exists so students are not disadvantaged if they choose not to use AI.
Original evidence and scope
Under Senate Policy DocID 79331 §2.1.1(c), assessments designated as Category C (AI Permitted) allow students to use AI tools for wider tasks, but require assessment briefs to state which tools and outputs are allowed, mandate that submitted text must be authentic student work, and require that a non-AI pathway exists so students are not disadvantaged if they choose not to use AI.
clm-man-cat-permitted
Category C AI Permitted definition and non-use pathway requirement
c) AI Permitted: AI may be used to complete the assessment. The assessment information must set out what is acceptable AI use. The assessment brief should explain how students who do not wish to personally use AI tools can undertake the assessment.
Section 2.1.1(c), Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 147–150; characters 8686–8975; excerpt offset 0–289
Official university source ↗
Under Senate Policy DocID 79331 §2.1.1(d), assessments designated as Category D (AI-Integrated) require students to use AI tools to achieve the unit's intended learning outcomes, with the assessment brief detailing the tools, permitted uses, reflection, and logging requirements.
Original evidence and scope
Under Senate Policy DocID 79331 §2.1.1(d), assessments designated as Category D (AI-Integrated) require students to use AI tools to achieve the unit's intended learning outcomes, with the assessment brief detailing the tools, permitted uses, reflection, and logging requirements.
clm-man-cat-integrated
Category D AI-Integrated definition and learning outcome alignment
d) AI-Integrated: AI use is necessary to meet the course unit intended learning outcomes. This does not imply that all AI use is permitted. The assessment information must set out what is acceptable AI use and should explain why AI use is required to meet the intended learning outcomes.
Section 2.1.1(d), Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 152–155; characters 8985–9305; excerpt offset 0–320
Official university source ↗
Under Senate Policy DocID 79331 §2.1.2, students may choose not to use AI for assessment, unless the assessment has been designated as Category D (AI-Integrated); students in Categories A, B, and C who choose not to use AI will not be disadvantaged.
Original evidence and scope
Under Senate Policy DocID 79331 §2.1.2, students may choose not to use AI for assessment, unless the assessment has been designated as Category D (AI-Integrated); students in Categories A, B, and C who choose not to use AI will not be disadvantaged.
clm-man-student-choice-category-b-c
Student choice not to use AI restricted to Categories A, B, C and explicitly excluding Category D
2.1.2 Students may choose not to use AI for assessment, unless the assessment has been designated as Category D.
Section 2.1.2, Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 158–159; characters 9308–9430; excerpt offset 0–122
Official university source ↗
b) AI Minimal: AI is permitted to be used in this assessment in limited ways that contribute to the presentation (for example surface level use to improve grammar, fluency, and formatting) without changing the ideas, arguments or conclusions developed by the student. The assessment information must set out what is acceptable AI use. Students who do not wish to personally use AI tools can undertake the assessment.
Section 2.1.1(b), Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 140–145; characters 8205–8676; excerpt offset 0–471
Official university source ↗
c) AI Permitted: AI may be used to complete the assessment. The assessment information must set out what is acceptable AI use. The assessment brief should explain how students who do not wish to personally use AI tools can undertake the assessment.
Section 2.1.1(c), Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 147–150; characters 8686–8975; excerpt offset 0–289
Official university source ↗
Under Senate Policy DocID 79331 §2.1.3, the designated AI category for every assessment must be clearly communicated to students in the Course Unit Specification and within the assessment brief on the virtual learning environment (Canvas).
Original evidence and scope
Under Senate Policy DocID 79331 §2.1.3, the designated AI category for every assessment must be clearly communicated to students in the Course Unit Specification and within the assessment brief on the virtual learning environment (Canvas).
clm-man-assessment-brief-comms
Mandatory publication of AI category in unit specifications and Canvas briefs
2.1.3 Information relating to the category of AI use for the assessment must be clearly communicated to students and included in the assessment brief and unit specification.
Section 2.1.3, Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 161–163; characters 9432–9623; excerpt offset 0–191
Official university source ↗
Acknowledge AI use following University Library guidance: cite direct text/image use formally, provide an overview acknowledgement when asked or appropriate, and include prompts/outputs in an appendix when referencing AI as personal communication or required by School instructions.
Source guidance
Acknowledge AI use following University Library guidance: cite direct text/image use formally, provide an overview acknowledgement when asked or appropriate, and include prompts/outputs in an appendix when referencing AI as personal communication or required by School instructions.
Scope
Audience and activity scope varies strictly by source: Senate Policy DocID 79331 governs taught assessment categorization (Categories A–D) and copyright upload restrictions; Library referencing guidance governs citation and acknowledgement in coursework; Academic Malpractice Procedure DocID 639 governs malpractice investigations, detector prohibition, and authorship vivas; IT Services policies govern Copilot and NebulaONE tenant access.
Under University Library 'AI and referencing' guidance, students must cite generative AI tools when using their text or images directly in work; where asked or appropriate, students should provide an overview acknowledgement at the start of work or in a footnote; and when referencing AI as personal communication or instructed by their School, students should provide relevant prompts/outputs in an appendix, generation dates, and a modification statement. Basic grammar and spell checking tools do not require acknowledgement unless School guidance requires it.
Original evidence and scope
Under University Library 'AI and referencing' guidance, students must cite generative AI tools when using their text or images directly in work; where asked or appropriate, students should provide an overview acknowledgement at the start of work or in a footnote; and when referencing AI as personal communication or instructed by their School, students should provide relevant prompts/outputs in an appendix, generation dates, and a modification statement. Basic grammar and spell checking tools do not require acknowledgement unless School guidance requires it.
CL-010
Library referencing guidance: in-text citation for direct text/image use, overview acknowledgement when asked or appropriate, appendix when referencing as personal communication or requested by School, and basic spelling/grammar exemption
You must cite or acknowledge the outputs of generative AI tools when you use them in your work.
Referencing AI > When to cite; Extracted text SHA256 b5072bc3c9b03215592dbbf6a179ea9b28fb1faf3b87136f0c7cef2987f5737a; original binding lines 69–69; characters 5653–5748; excerpt offset 0–95
Official university source ↗
Basic grammar and spell-checking Using AI-powered tools like Grammarly or MS Word’s Editor for grammar and spelling corrections does not need acknowledgement.
Referencing AI > Basic grammar and spell-checking; Extracted text SHA256 b5072bc3c9b03215592dbbf6a179ea9b28fb1faf3b87136f0c7cef2987f5737a; original binding lines 153–154; characters 13670–13828; excerpt offset 0–158
Official university source ↗
Disclaimer: A citation may not be needed for these examples but you should check with your School guidance in case you are required to acknowledge how you have used them.
Referencing AI > Citation disclaimer; Extracted text SHA256 b5072bc3c9b03215592dbbf6a179ea9b28fb1faf3b87136f0c7cef2987f5737a; original binding lines 150–150; characters 13253–13423; excerpt offset 0–170
Official university source ↗
When using AI tools, you should ensure that you reference them appropriately. If you use an AI tool (such as a chatbot, image generator or other AI system) and use the text or image directly in your work, you will need to cite it.
AI and referencing > How to reference an AI tool, Paragraph 1, Line 41; Extracted text SHA256 b5072bc3c9b03215592dbbf6a179ea9b28fb1faf3b87136f0c7cef2987f5737a; original binding lines 41–41; characters 2478–2708; excerpt offset 0–230
Official university source ↗
Acknowledging your use of an AI tool You may be asked or feel it is appropriate to acknowledge your use of an AI tool or system. This acknowledgement can sit at the start of your work (or sometimes be found in a footnote) and would usually give an overview of the tools used and the outputs.
AI and referencing > Acknowledging your use of an AI tool, Lines 62–63; Extracted text SHA256 b5072bc3c9b03215592dbbf6a179ea9b28fb1faf3b87136f0c7cef2987f5737a; original binding lines 62–63; characters 4773–5064; excerpt offset 0–291
Official university source ↗
Referencing an AI tool as personal communication All the relevant prompts and outputs generated from the interaction in the form of an appendix. Date when the outputs were generated. A statement on any modifications that were applied to the output which were included in a piece of work.
AI and referencing > Referencing an AI tool as personal communication, Lines 65–68; Extracted text SHA256 b5072bc3c9b03215592dbbf6a179ea9b28fb1faf3b87136f0c7cef2987f5737a; original binding lines 65–68; characters 5365–5652; excerpt offset 0–287
Official university source ↗
Use your University IT account to access Microsoft Copilot Chat for commercial data protection; if uploading taught session recordings for study assistance, use University-provided Microsoft 365 Copilot (DocID 79331 §2.2.2).
Source guidance
Use your University IT account to access Microsoft Copilot Chat for commercial data protection; if uploading taught session recordings for study assistance, use University-provided Microsoft 365 Copilot (DocID 79331 §2.2.2).
Scope
Audience and activity scope varies strictly by source: Senate Policy DocID 79331 governs taught assessment categorization (Categories A–D) and copyright upload restrictions; Library referencing guidance governs citation and acknowledgement in coursework; Academic Malpractice Procedure DocID 639 governs malpractice investigations, detector prohibition, and authorship vivas; IT Services policies govern Copilot and NebulaONE tenant access.
The University of Manchester announced a strategic collaboration with Microsoft to deploy equitable AI tools, providing Copilot Chat to all students and staff, and progressing a phased rollout of Microsoft 365 Copilot licenses across 65,000 colleagues and students.
Original evidence and scope
The University of Manchester announced a strategic collaboration with Microsoft to deploy equitable AI tools, providing Copilot Chat to all students and staff, and progressing a phased rollout of Microsoft 365 Copilot licenses across 65,000 colleagues and students.
CL-003
Institutional software deployment; phased licensing rollout alongside universal Copilot Chat
The University has announced a strategic collaboration with Microsoft, making Manchester the world’s first university to deploy equitable Microsoft 365 Copilot access and training across its entire community. This means 65,000 colleagues and students will benefit from the full Microsoft 365 Copilot suite. The deployment will support learning, research and professional work, positioning Manchester at the forefront of responsible, large-scale adoption of artificial intelligence tools in higher education.
Approved Tools > Microsoft 365 Copilot License, Paragraphs 1-2; Extracted text SHA256 98c59a36e27fd1e3695ae939993035e6af146c44cc41b7f3f90ae7ec09b78202; original binding lines 33–34; characters 1116–1623; excerpt offset 0–507
Official university source ↗
The roll out of licenses will be phased and implementation planning is now underway. Visit the Microsoft 365 Copilot SharePoint space for guidance, FAQs, training and updates as the roll out continues.
Approved Tools > Microsoft 365 Copilot License, Paragraph 6; Extracted text SHA256 98c59a36e27fd1e3695ae939993035e6af146c44cc41b7f3f90ae7ec09b78202; original binding lines 38–38; characters 2692–2893; excerpt offset 0–201
Official university source ↗
Copilot Chat is an AI-powered assistant available to everyone with a University account and accessible via a web browser or within Microsoft Teams.
Approved Tools > Copilot Chat; Extracted text SHA256 98c59a36e27fd1e3695ae939993035e6af146c44cc41b7f3f90ae7ec09b78202; original binding lines 41–41; characters 2929–3076; excerpt offset 0–147
Official university source ↗
Copilot Chat is listed for The University of Manchester in an official university AI tools source. Derived availability: allowed. Derived endorsement type: institutionally licensed or procured.
Original evidence and scope
Copilot Chat is listed for The University of Manchester in an official university AI tools source. Derived availability: allowed. Derived endorsement type: institutionally licensed or procured.
cl-the-university-of-manchester-microsoft-copilot-206
Universal student and staff access to Microsoft Copilot Chat
Copilot Chat is an AI-powered assistant available to everyone with a University account and accessible via a web browser or within Microsoft Teams.
Approved Tools > Copilot Chat; Extracted text SHA256 98c59a36e27fd1e3695ae939993035e6af146c44cc41b7f3f90ae7ec09b78202; original binding lines 41–41; characters 2929–3076; excerpt offset 0–147
Official university source ↗
Microsoft 365 Copilot License is listed for The University of Manchester in an official university AI tools source. Derived availability: not mentioned. Derived endorsement type: officially endorsed.
Original evidence and scope
Microsoft 365 Copilot License is listed for The University of Manchester in an official university AI tools source. Derived availability: not mentioned. Derived endorsement type: officially endorsed.
cl-the-university-of-manchester-microsoft-copilot-for-m365-207
Microsoft 365 Copilot phased deployment and mandatory staff data protection scope
The University has announced a strategic collaboration with Microsoft, making Manchester the world’s first university to deploy equitable Microsoft 365 Copilot access and training across its entire community.
Approved Tools > Microsoft 365 Copilot License, Paragraph 1; Extracted text SHA256 98c59a36e27fd1e3695ae939993035e6af146c44cc41b7f3f90ae7ec09b78202; original binding lines 33–33; characters 1116–1324; excerpt offset 0–208
Official university source ↗
The roll out of licenses will be phased and implementation planning is now underway. Visit the Microsoft 365 Copilot SharePoint space for guidance, FAQs, training and updates as the roll out continues.
Approved Tools > Microsoft 365 Copilot License, Paragraph 6; Extracted text SHA256 98c59a36e27fd1e3695ae939993035e6af146c44cc41b7f3f90ae7ec09b78202; original binding lines 38–38; characters 2692–2893; excerpt offset 0–201
Official university source ↗
2.3.1 Staff members who use AI in Teaching and Learning activities must adhere to the University's AI Guidelines. Only the University-provided Microsoft 365 Copilot service may be used for student-identifiable or confidential data.
Section 2.3.1, Page 5; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 205–207; characters 11852–12101; excerpt offset 0–249
Official university source ↗
NebulaONE is listed for The University of Manchester in an official university AI tools source. Derived availability: conditionally allowed. Derived endorsement type: self hosted system.
Original evidence and scope
NebulaONE is listed for The University of Manchester in an official university AI tools source. Derived availability: conditionally allowed. Derived endorsement type: self hosted system.
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NebulaONE high-performance AI sandbox for researchers and staff
NebulaONE is an AI toolbox built within UoM’s cloud environment. It uses market-leading models to help you create custom AI agents, no coding required. Whether you're in research, teaching, or professional services, NebulaONE enables safe experimentation while ensuring full compliance with the University’s AI Guidelines.
Approved Tools > NebulaONE; Extracted text SHA256 98c59a36e27fd1e3695ae939993035e6af146c44cc41b7f3f90ae7ec09b78202; original binding lines 71–72; characters 6162–6484; excerpt offset 0–322
Official university source ↗
We have recently started onboarding early adopters to test the NebulaONE AI system. If you’re interested in gaining early access, please sign up using the Nebula One Request Form.
Approved Tools > NebulaONE > Early Access Opportunity; Extracted text SHA256 98c59a36e27fd1e3695ae939993035e6af146c44cc41b7f3f90ae7ec09b78202; original binding lines 80–80; characters 7205–7384; excerpt offset 0–179
Official university source ↗
Under StaffNet Teaching and Learning Guidelines, where AI use is encouraged or required, the University must ensure all students have equitable access at no additional cost or provide an alternative mechanism that avoids requiring students to provide personal data to third parties.
Original evidence and scope
Under StaffNet Teaching and Learning Guidelines, where AI use is encouraged or required, the University must ensure all students have equitable access at no additional cost or provide an alternative mechanism that avoids requiring students to provide personal data to third parties.
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Equitable access commitment at no additional cost and alternative mechanism for third-party personal data protection
Where the use of AI is encouraged or required, the University must ensure students have equitable access to tools at no additional cost to themselves. Where the use of AI requires students to provide personal data to a third party, an alternative mechanism must be available that does not disadvantage any student who declines to provide such data. Students must be made aware of how third-party systems use their data, including their authored prompts and other uploaded content.
Teaching and Learning > Access and choice; Extracted text SHA256 6ca485f22cb29ccf5fe174cc9ee2437d2543ed93b82235be305e3df79d901fb9; original binding lines 81–81; characters 7507–7987; excerpt offset 0–480
Official university source ↗

Don’t

Never upload University copyright materials—including lecture recordings, slides, handouts, and exam questions—to external AI tools (DocID 79331 §2.2.1(c)); teaching staff handling student-identifiable data must exclusively use M365 Copilot (§2.3.1).
Source guidance
Never upload University copyright materials—including lecture recordings, slides, handouts, and exam questions—to external AI tools (DocID 79331 §2.2.1(c)); teaching staff handling student-identifiable data must exclusively use M365 Copilot (§2.3.1).
Scope
Audience and activity scope varies strictly by source: Senate Policy DocID 79331 governs taught assessment categorization (Categories A–D) and copyright upload restrictions; Library referencing guidance governs citation and acknowledgement in coursework; Academic Malpractice Procedure DocID 639 governs malpractice investigations, detector prohibition, and authorship vivas; IT Services policies govern Copilot and NebulaONE tenant access.
When using Copilot Chat with a University account, interactions are private, data is protected by Commercial Data Protection, prompts are not used to train AI models, uploaded files are stored in user OneDrive, and web searches over Bing transmit query fragments without user identity.
Original evidence and scope
When using Copilot Chat with a University account, interactions are private, data is protected by Commercial Data Protection, prompts are not used to train AI models, uploaded files are stored in user OneDrive, and web searches over Bing transmit query fragments without user identity.
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Copilot Chat Commercial Data Protection technical parameters and Bing search privacy
Copilot Chat is an AI-powered assistant available to everyone with a University account and accessible via a web browser or within Microsoft Teams. Guidance For Using Copilot Chat The University of Manchester has contractual agreement with Microsoft that means that the Copilot Chat Generative AI system can be used safely be as part of your day-to-day work in a way that is not true for other AI chat systems.
Approved Tools > Copilot Chat > What Is Copilot Chat?; Extracted text SHA256 98c59a36e27fd1e3695ae939993035e6af146c44cc41b7f3f90ae7ec09b78202; original binding lines 41–43; characters 2929–3339; excerpt offset 0–410
Official university source ↗
Sometimes Copilot Chat may search the web using Microsoft’s search engine Bing in order to find information that is relevant to your prompt. When this occurs, fragments of your prompt may be sent to Bing. There is no way to prevent this from happening, however your identity is not shared, and the query is sent over a secure connection.
Approved Tools > Copilot Chat > Web searches; Extracted text SHA256 98c59a36e27fd1e3695ae939993035e6af146c44cc41b7f3f90ae7ec09b78202; original binding lines 61–61; characters 4893–5230; excerpt offset 0–337
Official university source ↗
University members must apply standard data protection rules to AI tools; under Senate Policy DocID 79331 §2.3.1, staff members who use AI in Teaching and Learning activities must exclusively use the University-provided Microsoft 365 Copilot service when handling student-identifiable or confidential data, and under §2.2.1(c) students must not upload University copyright materials to external AI.
Original evidence and scope
University members must apply standard data protection rules to AI tools; under Senate Policy DocID 79331 §2.3.1, staff members who use AI in Teaching and Learning activities must exclusively use the University-provided Microsoft 365 Copilot service when handling student-identifiable or confidential data, and under §2.2.1(c) students must not upload University copyright materials to external AI.
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Data classification, confidential information protection, mandatory staff M365 Copilot usage for student data in teaching/learning, and student copyright upload bans
you should use University-approved tools wherever possible to avoid inappropriate disclosure; if you use other tools you are responsible for ensuring there is no inappropriate disclosure.
Applying the Principles; Extracted text SHA256 6ca485f22cb29ccf5fe174cc9ee2437d2543ed93b82235be305e3df79d901fb9; original binding lines 67–68; characters 5124–5311; excerpt offset 0–187
Official university source ↗
2.3.1 Staff members who use AI in Teaching and Learning activities must adhere to the University's AI Guidelines. Only the University-provided Microsoft 365 Copilot service may be used for student-identifiable or confidential data.
Section 2.3.1, Page 5; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 205–207; characters 11852–12101; excerpt offset 0–249
Official university source ↗
c) The University’s Intellectual Property Policy. Students must not upload any University of Manchester owned materials, including lecture – recordings, slides, question papers, handouts or any other copyrighted resources to external AI tools.
Section 2.2.1(c), Page 5; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 189–192; characters 10834–11110; excerpt offset 0–276
Official university source ↗
Microsoft 365 Copilot License is listed for The University of Manchester in an official university AI tools source. Derived availability: not mentioned. Derived endorsement type: officially endorsed.
Original evidence and scope
Microsoft 365 Copilot License is listed for The University of Manchester in an official university AI tools source. Derived availability: not mentioned. Derived endorsement type: officially endorsed.
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Microsoft 365 Copilot phased deployment and mandatory staff data protection scope
The University has announced a strategic collaboration with Microsoft, making Manchester the world’s first university to deploy equitable Microsoft 365 Copilot access and training across its entire community.
Approved Tools > Microsoft 365 Copilot License, Paragraph 1; Extracted text SHA256 98c59a36e27fd1e3695ae939993035e6af146c44cc41b7f3f90ae7ec09b78202; original binding lines 33–33; characters 1116–1324; excerpt offset 0–208
Official university source ↗
The roll out of licenses will be phased and implementation planning is now underway. Visit the Microsoft 365 Copilot SharePoint space for guidance, FAQs, training and updates as the roll out continues.
Approved Tools > Microsoft 365 Copilot License, Paragraph 6; Extracted text SHA256 98c59a36e27fd1e3695ae939993035e6af146c44cc41b7f3f90ae7ec09b78202; original binding lines 38–38; characters 2692–2893; excerpt offset 0–201
Official university source ↗
2.3.1 Staff members who use AI in Teaching and Learning activities must adhere to the University's AI Guidelines. Only the University-provided Microsoft 365 Copilot service may be used for student-identifiable or confidential data.
Section 2.3.1, Page 5; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 205–207; characters 11852–12101; excerpt offset 0–249
Official university source ↗
Under Senate Policy DocID 79331 §2.2.1(c), students must not upload any University of Manchester-owned copyright materials—such as lecture recordings, PowerPoint slides, handouts, and examination question papers—to external commercial AI tools.
Original evidence and scope
Under Senate Policy DocID 79331 §2.2.1(c), students must not upload any University of Manchester-owned copyright materials—such as lecture recordings, PowerPoint slides, handouts, and examination question papers—to external commercial AI tools.
clm-man-copyright-upload-restriction
Strict ban on uploading University copyright materials to external commercial AI tools
c) The University’s Intellectual Property Policy. Students must not upload any University of Manchester owned materials, including lecture – recordings, slides, question papers, handouts or any other copyrighted resources to external AI tools.
Section 2.2.1(c), Page 5; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 189–192; characters 10834–11110; excerpt offset 0–276
Official university source ↗
Under Senate Policy DocID 79331 §2.2.2, students are explicitly permitted to upload session recordings into the University-provided Microsoft 365 Copilot service to ask questions or create study summaries.
Original evidence and scope
Under Senate Policy DocID 79331 §2.2.2, students are explicitly permitted to upload session recordings into the University-provided Microsoft 365 Copilot service to ask questions or create study summaries.
clm-man-copilot-recording-safe-harbor
Explicit safe-harbor exception permitting session recording uploads to institutional M365 Copilot
2.2.2 Where a recording of a taught session is available, students are permitted to use their University of Manchester Microsoft 365 Copilot access to upload this for the purposes of supporting their learning. Uploading University of Manchester – owned materials to the University of Manchester Microsoft 365 Copilot will not contravene the Intellectual Property Policy providing students use their University-provided access. Further information about lecture recordings is available in the Policy on Recording Lectures.
Section 2.2.2, Page 5; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 196–201; characters 11217–11780; excerpt offset 0–563
Official university source ↗
Under Senate Policy DocID 79331 §2.3.1, staff members who use AI in Teaching and Learning activities must adhere to the University's AI Guidelines, and only the University-provided Microsoft 365 Copilot service may be used for student-identifiable or confidential data.
Original evidence and scope
Under Senate Policy DocID 79331 §2.3.1, staff members who use AI in Teaching and Learning activities must adhere to the University's AI Guidelines, and only the University-provided Microsoft 365 Copilot service may be used for student-identifiable or confidential data.
clm-man-staff-confidential-data-copilot
Mandatory restriction on staff members in teaching and learning activities using student-identifiable or confidential data exclusively with institutional Microsoft 365 Copilot
2.3.1 Staff members who use AI in Teaching and Learning activities must adhere to the University's AI Guidelines. Only the University-provided Microsoft 365 Copilot service may be used for student-identifiable or confidential data.
Section 2.3.1, Page 5; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 205–207; characters 11852–12101; excerpt offset 0–249
Official university source ↗
Do not use generative AI in Category A (Prohibited) assessments (even for proofreading or spelling/grammar correction), or beyond surface presentation in Category B (Minimal); note that student choice not to use AI does not apply to Category D (Integrated).
Source guidance
Do not use generative AI in Category A (Prohibited) assessments (even for proofreading or spelling/grammar correction), or beyond surface presentation in Category B (Minimal); note that student choice not to use AI does not apply to Category D (Integrated).
Scope
Audience and activity scope varies strictly by source: Senate Policy DocID 79331 governs taught assessment categorization (Categories A–D) and copyright upload restrictions; Library referencing guidance governs citation and acknowledgement in coursework; Academic Malpractice Procedure DocID 639 governs malpractice investigations, detector prohibition, and authorship vivas; IT Services policies govern Copilot and NebulaONE tenant access.
Under Senate Policy DocID 79331 §2.1.1, all coursework assessments must be assigned to one of four AI categories (A: AI Prohibited, B: AI Minimal, C: AI Permitted, D: AI-Integrated); under §2.1.2 students may choose not to use AI in Categories A, B, and C (excluding Category D), and under §2.1.3 the category must be published in unit specifications and assessment briefs.
Original evidence and scope
Under Senate Policy DocID 79331 §2.1.1, all coursework assessments must be assigned to one of four AI categories (A: AI Prohibited, B: AI Minimal, C: AI Permitted, D: AI-Integrated); under §2.1.2 students may choose not to use AI in Categories A, B, and C (excluding Category D), and under §2.1.3 the category must be published in unit specifications and assessment briefs.
CL-008
Senate-approved four-tier assessment categorization framework across all course units
The University has produced a dedicated AI in Teaching and Learning Policy which sets out a shared framework for the use of AI in assessment at the University, defining clear and transparent expectations for students and staff when using AI across undergraduate and postgraduate teaching, learning, assessment, and research or dissertation activities.
Teaching and Learning > Assessment; Extracted text SHA256 6ca485f22cb29ccf5fe174cc9ee2437d2543ed93b82235be305e3df79d901fb9; original binding lines 75–75; characters 6291–6642; excerpt offset 0–351
Official university source ↗
a) AI Prohibited: AI is not permitted or is unable to be used in this assessment. The assessment information should include additional information such as examples or detail of what is not permitted, if it is likely to provide clarity for students.
Section 2.1.1(a), Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 136–138; characters 7925–8195; excerpt offset 0–270
Official university source ↗
b) AI Minimal: AI is permitted to be used in this assessment in limited ways that contribute to the presentation (for example surface level use to improve grammar, fluency, and formatting) without changing the ideas, arguments or conclusions developed by the student. The assessment information must set out what is acceptable AI use. Students who do not wish to personally use AI tools can undertake the assessment.
Section 2.1.1(b), Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 140–145; characters 8205–8676; excerpt offset 0–471
Official university source ↗
c) AI Permitted: AI may be used to complete the assessment. The assessment information must set out what is acceptable AI use. The assessment brief should explain how students who do not wish to personally use AI tools can undertake the assessment.
Section 2.1.1(c), Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 147–150; characters 8686–8975; excerpt offset 0–289
Official university source ↗
d) AI-Integrated: AI use is necessary to meet the course unit intended learning outcomes. This does not imply that all AI use is permitted. The assessment information must set out what is acceptable AI use and should explain why AI use is required to meet the intended learning outcomes.
Section 2.1.1(d), Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 152–155; characters 8985–9305; excerpt offset 0–320
Official university source ↗
2.1.2 Students may choose not to use AI for assessment, unless the assessment has been designated as Category D.
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Official university source ↗
2.1.3 Information relating to the category of AI use for the assessment must be clearly communicated to students and included in the assessment brief and unit specification.
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Official university source ↗
Under Senate Policy DocID 79331 §2.1.1, using an AI tool to assist with grammar, fluency, or spelling is permitted in Category B (AI Minimal) assessments provided it does not alter student ideas, arguments, or conclusions, but AI proofreading is not permitted in Category A (AI Prohibited) assessments.
Original evidence and scope
Under Senate Policy DocID 79331 §2.1.1, using an AI tool to assist with grammar, fluency, or spelling is permitted in Category B (AI Minimal) assessments provided it does not alter student ideas, arguments, or conclusions, but AI proofreading is not permitted in Category A (AI Prohibited) assessments.
CL-009
Assessment-category bounds on proofreading: permitted in Category B for presentation only without altering ideas, strictly prohibited in Category A
a) AI Prohibited: AI is not permitted or is unable to be used in this assessment. The assessment information should include additional information such as examples or detail of what is not permitted, if it is likely to provide clarity for students.
Section 2.1.1(a), Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 136–138; characters 7925–8195; excerpt offset 0–270
Official university source ↗
b) AI Minimal: AI is permitted to be used in this assessment in limited ways that contribute to the presentation (for example surface level use to improve grammar, fluency, and formatting) without changing the ideas, arguments or conclusions developed by the student. The assessment information must set out what is acceptable AI use. Students who do not wish to personally use AI tools can undertake the assessment.
Section 2.1.1(b), Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 140–145; characters 8205–8676; excerpt offset 0–471
Official university source ↗
Using an AI tool to correct grammar or spelling is acceptable, but where a student uses an AI tool for proofreading work submitted for assessment, they should ensure that use of the tool does not result in substantive changes to the content or meaning of their work or go beyond what is allowed for the assessment.
Teaching and Learning > Proofreading; Extracted text SHA256 6ca485f22cb29ccf5fe174cc9ee2437d2543ed93b82235be305e3df79d901fb9; original binding lines 79–79; characters 7174–7488; excerpt offset 0–314
Official university source ↗
Under Senate Policy DocID 79331 §2.1.1(a), assessments designated as Category A (AI Prohibited) completely forbid using AI tools to assist in the preparation or writing of the submission, including for generating content or for proofreading / editing text, and the assessment brief must explain why this prohibition is in place.
Original evidence and scope
Under Senate Policy DocID 79331 §2.1.1(a), assessments designated as Category A (AI Prohibited) completely forbid using AI tools to assist in the preparation or writing of the submission, including for generating content or for proofreading / editing text, and the assessment brief must explain why this prohibition is in place.
clm-man-cat-prohibited
Category A AI Prohibited definition and mandatory assessment brief details
a) AI Prohibited: AI is not permitted or is unable to be used in this assessment. The assessment information should include additional information such as examples or detail of what is not permitted, if it is likely to provide clarity for students.
Section 2.1.1(a), Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 136–138; characters 7925–8195; excerpt offset 0–270
Official university source ↗
Under Senate Policy DocID 79331 §2.1.1(b), assessments designated as Category B (AI Minimal) permit using AI tools only in relation to presentation—such as to improve fluency, grammar, or spelling, or to assist with formatting—and strictly forbid using AI tools to generate ideas, arguments, conclusions, or other substantive content.
Original evidence and scope
Under Senate Policy DocID 79331 §2.1.1(b), assessments designated as Category B (AI Minimal) permit using AI tools only in relation to presentation—such as to improve fluency, grammar, or spelling, or to assist with formatting—and strictly forbid using AI tools to generate ideas, arguments, conclusions, or other substantive content.
clm-man-cat-minimal
Category B AI Minimal definition and presentation-only boundary
b) AI Minimal: AI is permitted to be used in this assessment in limited ways that contribute to the presentation (for example surface level use to improve grammar, fluency, and formatting) without changing the ideas, arguments or conclusions developed by the student. The assessment information must set out what is acceptable AI use. Students who do not wish to personally use AI tools can undertake the assessment.
Section 2.1.1(b), Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 140–145; characters 8205–8676; excerpt offset 0–471
Official university source ↗
Under Senate Policy DocID 79331 §2.1.1(c), assessments designated as Category C (AI Permitted) allow students to use AI tools for wider tasks, but require assessment briefs to state which tools and outputs are allowed, mandate that submitted text must be authentic student work, and require that a non-AI pathway exists so students are not disadvantaged if they choose not to use AI.
Original evidence and scope
Under Senate Policy DocID 79331 §2.1.1(c), assessments designated as Category C (AI Permitted) allow students to use AI tools for wider tasks, but require assessment briefs to state which tools and outputs are allowed, mandate that submitted text must be authentic student work, and require that a non-AI pathway exists so students are not disadvantaged if they choose not to use AI.
clm-man-cat-permitted
Category C AI Permitted definition and non-use pathway requirement
c) AI Permitted: AI may be used to complete the assessment. The assessment information must set out what is acceptable AI use. The assessment brief should explain how students who do not wish to personally use AI tools can undertake the assessment.
Section 2.1.1(c), Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 147–150; characters 8686–8975; excerpt offset 0–289
Official university source ↗
Under Senate Policy DocID 79331 §2.1.1(d), assessments designated as Category D (AI-Integrated) require students to use AI tools to achieve the unit's intended learning outcomes, with the assessment brief detailing the tools, permitted uses, reflection, and logging requirements.
Original evidence and scope
Under Senate Policy DocID 79331 §2.1.1(d), assessments designated as Category D (AI-Integrated) require students to use AI tools to achieve the unit's intended learning outcomes, with the assessment brief detailing the tools, permitted uses, reflection, and logging requirements.
clm-man-cat-integrated
Category D AI-Integrated definition and learning outcome alignment
d) AI-Integrated: AI use is necessary to meet the course unit intended learning outcomes. This does not imply that all AI use is permitted. The assessment information must set out what is acceptable AI use and should explain why AI use is required to meet the intended learning outcomes.
Section 2.1.1(d), Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 152–155; characters 8985–9305; excerpt offset 0–320
Official university source ↗
Under Senate Policy DocID 79331 §2.1.2, students may choose not to use AI for assessment, unless the assessment has been designated as Category D (AI-Integrated); students in Categories A, B, and C who choose not to use AI will not be disadvantaged.
Original evidence and scope
Under Senate Policy DocID 79331 §2.1.2, students may choose not to use AI for assessment, unless the assessment has been designated as Category D (AI-Integrated); students in Categories A, B, and C who choose not to use AI will not be disadvantaged.
clm-man-student-choice-category-b-c
Student choice not to use AI restricted to Categories A, B, C and explicitly excluding Category D
2.1.2 Students may choose not to use AI for assessment, unless the assessment has been designated as Category D.
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Official university source ↗
b) AI Minimal: AI is permitted to be used in this assessment in limited ways that contribute to the presentation (for example surface level use to improve grammar, fluency, and formatting) without changing the ideas, arguments or conclusions developed by the student. The assessment information must set out what is acceptable AI use. Students who do not wish to personally use AI tools can undertake the assessment.
Section 2.1.1(b), Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 140–145; characters 8205–8676; excerpt offset 0–471
Official university source ↗
c) AI Permitted: AI may be used to complete the assessment. The assessment information must set out what is acceptable AI use. The assessment brief should explain how students who do not wish to personally use AI tools can undertake the assessment.
Section 2.1.1(c), Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 147–150; characters 8686–8975; excerpt offset 0–289
Official university source ↗
Under Senate Policy DocID 79331 §2.1.3, the designated AI category for every assessment must be clearly communicated to students in the Course Unit Specification and within the assessment brief on the virtual learning environment (Canvas).
Original evidence and scope
Under Senate Policy DocID 79331 §2.1.3, the designated AI category for every assessment must be clearly communicated to students in the Course Unit Specification and within the assessment brief on the virtual learning environment (Canvas).
clm-man-assessment-brief-comms
Mandatory publication of AI category in unit specifications and Canvas briefs
2.1.3 Information relating to the category of AI use for the assessment must be clearly communicated to students and included in the assessment brief and unit specification.
Section 2.1.3, Page 4; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 161–163; characters 9432–9623; excerpt offset 0–191
Official university source ↗
Do not present unacknowledged AI-generated content as your own (an indicator of academic malpractice under DocID 639 §3.1.3.6); markers rely on academic judgement and Turnitin similarity as the University does not use software claiming to detect GenAI (§4.2.2).
Source guidance
Do not present unacknowledged AI-generated content as your own (an indicator of academic malpractice under DocID 639 §3.1.3.6); markers rely on academic judgement and Turnitin similarity as the University does not use software claiming to detect GenAI (§4.2.2).
Scope
Audience and activity scope varies strictly by source: Senate Policy DocID 79331 governs taught assessment categorization (Categories A–D) and copyright upload restrictions; Library referencing guidance governs citation and acknowledgement in coursework; Academic Malpractice Procedure DocID 639 governs malpractice investigations, detector prohibition, and authorship vivas; IT Services policies govern Copilot and NebulaONE tenant access.
Submitting work created by generative AI as one's own, or misrepresenting understanding of the subject, is plagiarism at Manchester and will be dealt with in accordance with the University's Academic Malpractice Procedure.
Original evidence and scope
Submitting work created by generative AI as one's own, or misrepresenting understanding of the subject, is plagiarism at Manchester and will be dealt with in accordance with the University's Academic Malpractice Procedure.
CL-006
Definition of AI academic malpractice and formal plagiarism indicators
There is an expectation that work submitted by a student for assessment should contain their own original work and provide an honest representation of their understanding of the subject. Students should declare any use of generative AI in preparing work for assessment, and explain its role. Submitting work created by Generative AI as their own, or to misrepresent their understanding of the subject, is plagiarism and will be dealt with in accordance with the University’s Academic Malpractice Procedure.
Teaching and Learning > Plagiarism; Extracted text SHA256 6ca485f22cb29ccf5fe174cc9ee2437d2543ed93b82235be305e3df79d901fb9; original binding lines 77–77; characters 6654–7160; excerpt offset 0–506
Official university source ↗
3.1.3.6. The use of content generated by AI and failing to acknowledge this
Section 3.1.3 Indicators of academic malpractice, Paragraph 3.1.3.6, Page 4; Extracted text SHA256 db1ed4db97896ef1f771a937943e2402de1a954b0b0a56c53a781efa68c9af77; original binding lines 233–233; characters 14230–14307; excerpt offset 0–77
Official university source ↗
Tools to detect AI-generated content are unreliable and biased and cannot be relied on to identify academic malpractice in summative assessment at Manchester. Output from such tools cannot currently be used as evidence of malpractice.
Original evidence and scope
Tools to detect AI-generated content are unreliable and biased and cannot be relied on to identify academic malpractice in summative assessment at Manchester. Output from such tools cannot currently be used as evidence of malpractice.
CL-007
Prohibition on commercial AI detection software and sole evidentiary role of academic judgement
Tools to detect AI-generated content are unreliable and biased and cannot be relied on to identify academic malpractice in summative assessment. Output from such tools cannot currently be used as evidence of malpractice.
Teaching and Learning > Detecting malpractice; Extracted text SHA256 6ca485f22cb29ccf5fe174cc9ee2437d2543ed93b82235be305e3df79d901fb9; original binding lines 83–83; characters 8010–8230; excerpt offset 0–220
Official university source ↗
The University does not currently use software which claims to detect Generative AI;
Section 4.2 Detection: Written assignments, Paragraph 4.2.2, Page 7; Extracted text SHA256 db1ed4db97896ef1f771a937943e2402de1a954b0b0a56c53a781efa68c9af77; original binding lines 369–370; characters 23487–23584; excerpt offset 0–97
Official university source ↗
Under Academic Malpractice Procedure DocID 639 §3.1.3.6 and Senate Policy DocID 79331 §3.0.2, using content generated by Artificial Intelligence without acknowledgement is explicitly designated as an indicator of academic malpractice and plagiarism.
Original evidence and scope
Under Academic Malpractice Procedure DocID 639 §3.1.3.6 and Senate Policy DocID 79331 §3.0.2, using content generated by Artificial Intelligence without acknowledgement is explicitly designated as an indicator of academic malpractice and plagiarism.
clm-man-malpractice-procedure-plagiarism
Formal definition of unacknowledged AI content generation as academic malpractice
3.1.3.6. The use of content generated by AI and failing to acknowledge this
Section 3.1.3 Indicators of academic malpractice, Paragraph 3.1.3.6, Page 4; Extracted text SHA256 db1ed4db97896ef1f771a937943e2402de1a954b0b0a56c53a781efa68c9af77; original binding lines 233–233; characters 14230–14307; excerpt offset 0–77
Official university source ↗
3.0.2 Within assessed work, students’ failure to document use of Generative AI could be a form of plagiarism contrary to the Academic Malpractice Procedure. Failure to adhere to the terms of an assessment brief is handled on an assessment-by-assessment basis and may be accounted for through the marking process.
Section 3.0.2, Page 6; Extracted text SHA256 b745f89ff007498a4675a6efa8e0c6ad5929094287f290525416791f177bb011; original binding lines 226–229; characters 12856–13206; excerpt offset 0–350
Official university source ↗
Under Academic Malpractice Procedure DocID 639 §4.2.2, the University explicitly does not use software that claims to detect Generative AI; Turnitin is used solely for text-matching similarity detection and cannot confirm whether malpractice occurred without marker academic judgement.
Original evidence and scope
Under Academic Malpractice Procedure DocID 639 §4.2.2, the University explicitly does not use software that claims to detect Generative AI; Turnitin is used solely for text-matching similarity detection and cannot confirm whether malpractice occurred without marker academic judgement.
clm-man-no-ai-detection-software
Prohibition on commercial AI detection tools and mandate for academic marker judgement
The University does not currently use software which claims to detect Generative AI;
Section 4.2 Detection: Written assignments, Paragraph 4.2.2, Page 7; Extracted text SHA256 db1ed4db97896ef1f771a937943e2402de1a954b0b0a56c53a781efa68c9af77; original binding lines 369–370; characters 23487–23584; excerpt offset 0–97
Official university source ↗
The University does not currently use software which claims to detect Generative AI;
Section 4.2 Detection: Written assignments, Paragraph 4.2.2; Extracted text SHA256 db1ed4db97896ef1f771a937943e2402de1a954b0b0a56c53a781efa68c9af77; original binding lines 369–370; characters 23487–23584; excerpt offset 0–97
Official university source ↗
Under Academic Malpractice Procedure DocID 639 §4.4.2, where indicators raise concerns of commissioned work without direct evidence, or available information does not satisfy the balance of probabilities, a viva voce can be arranged in agreement with the School Officer to demonstrate authorship; it does not contribute to the mark. If held, it should not normally take place more than 30 working days after the assessment feedback deadline (§4.4.3.1); the student should receive at least five working days notice explaining its nature, purpose and potential outcomes (§4.4.3.2). Accompaniment by a person of the student’s choice is for support only without participation (§4.4.3.4), and reasonable adjustments must be made (§4.4.3.5). The viva itself cannot impose a penalty (§4.4.4.2); case handling follows the applicable AUO/SDP/UDP procedures (§5.1–5.5).
Original evidence and scope
Under Academic Malpractice Procedure DocID 639 §4.4.2, where indicators raise concerns of commissioned work without direct evidence, or available information does not satisfy the balance of probabilities, a viva voce can be arranged in agreement with the School Officer to demonstrate authorship; it does not contribute to the mark. If held, it should not normally take place more than 30 working days after the assessment feedback deadline (§4.4.3.1); the student should receive at least five working days notice explaining its nature, purpose and potential outcomes (§4.4.3.2). Accompaniment by a person of the student’s choice is for support only without participation (§4.4.3.4), and reasonable adjustments must be made (§4.4.3.5). The viva itself cannot impose a penalty (§4.4.4.2); case handling follows the applicable AUO/SDP/UDP procedures (§5.1–5.5).
clm-man-authorship-viva-voce
Optional authorship viva voce trigger, 30-working-day post-feedback-deadline timing, 5-working-day notice, support-only accompaniment, reasonable adjustments, non-punitive viva outcome, and AUO case handling
4.4.2. If there is a concern, based on indicators of malpractice, that a student may have commissioned a piece of work from a third party, but there is no direct evidence of this, or the information available does not satisfy the balance of probabilities, then in agreement with the School Officer a viva voce can be arranged to give the student the opportunity to demonstrate that they: 4.4.2.1. Produced the work; 4.4.2.2. Undertook the reading and research themselves; 4.4.2.3. Undertook the preparatory work themselves; 4.4.2.4. Understand what they have written. 4.4.3. If a viva voce is held, the following principles
Section 4.4 Contract cheating, Paragraphs 4.4.2–4.4.3.4, Page 9; Extracted text SHA256 db1ed4db97896ef1f771a937943e2402de1a954b0b0a56c53a781efa68c9af77; original binding lines 484–518; characters 31340–33372; excerpt offset 0–700
Official university source ↗
shall be met: 4.4.3.1. If a viva voce is to be conducted it should not normally take place more than 30 working days after the assessment feedback deadline. 4.4.3.2. The student should be given at least five working days’ notice of the requirement to attend the viva voce. An explanation of what a viva voce is, the purpose of it and the potential outcomes should be outlined in the invitation. It should be made clear that the viva voce is arranged due to the detection of potential academic malpractice and it is to allow the student an opportunity to demonstrate that the work is their own; i
Section 4.4 Contract cheating, Paragraphs 4.4.2–4.4.3.4, Page 9; Extracted text SHA256 db1ed4db97896ef1f771a937943e2402de1a954b0b0a56c53a781efa68c9af77; original binding lines 484–518; characters 31340–33372; excerpt offset 700–1400
Official university source ↗
t will not contribute to any mark obtained for the piece of work. 4.4.3.3. Two members of academic staff (at least one of whom must be a subject specialist) must conduct the viva voce; this will normally be the School Officer and the examiner of the assessment. 4.4.3.4. The student may be accompanied by a person of their choice for support only (normally a fellow student, member of staff or Students’ Union representative). Any individual accompanying the student should under no circumstances participate in the viva voce.
Section 4.4 Contract cheating, Paragraphs 4.4.2–4.4.3.4, Page 9; Extracted text SHA256 db1ed4db97896ef1f771a937943e2402de1a954b0b0a56c53a781efa68c9af77; original binding lines 484–518; characters 31340–33372; excerpt offset 1400–2032
Official university source ↗
4.4.3.5. Reasonable adjustments must be made to ensure that candidates with additional support needs are not disadvantaged for reasons relating to a long-term medical condition, sensory impairment, specific learning difficulty and /or disability. 4.4.3.6. The viva voce will not normally exceed 45 minutes. 4.4.3.7. Depending on situational circumstances, the viva voce can be conducted via video link. 4.4.3.8. Intensive questions are expected. The questions asked should provide the student with the opportunity to demonstrate that the work is their own. 4.4.3.9. An accurate record
Section 4.4 Contract cheating, Paragraphs 4.4.3.5–4.4.4.2, Page 10; Extracted text SHA256 db1ed4db97896ef1f771a937943e2402de1a954b0b0a56c53a781efa68c9af77; original binding lines 523–549; characters 33484–35257; excerpt offset 0–700
Official university source ↗
of the viva voce should be taken; this record may be used to form the evidence base for any future disciplinary hearing. It may be necessary for an administrative member of staff to be present at the viva voce to make the record. The student is entitled to have a copy of the record. 4.4.4. The viva voce can have one of two outcomes: 4.4.4.1. The staff conducting the viva voce will confirm that they accept that the student wrote the work in question; no further action will be taken. The work should then be marked on its own merit, if it has not already been marked. 4.4.4.2. If the st
Section 4.4 Contract cheating, Paragraphs 4.4.3.5–4.4.4.2, Page 10; Extracted text SHA256 db1ed4db97896ef1f771a937943e2402de1a954b0b0a56c53a781efa68c9af77; original binding lines 523–549; characters 33484–35257; excerpt offset 700–1400
Official university source ↗
aff conducting the viva voce still remain doubtful of the authorship of the work in question, or the student admits that it is not their work, then the case should be referred for disciplinary action. The viva voce, in itself, will not result in a penalty being applied; a penalty can only be applied by a disciplinary panel.
Section 4.4 Contract cheating, Paragraphs 4.4.3.5–4.4.4.2, Page 10; Extracted text SHA256 db1ed4db97896ef1f771a937943e2402de1a954b0b0a56c53a781efa68c9af77; original binding lines 523–549; characters 33484–35257; excerpt offset 1400–1773
Official university source ↗
5.1. When academic malpractice has been identified following section 4 above, the AUO responsible for assessing the allegation should gather any supplementary information that may be relevant for a disciplinary hearing. In particular, they should enquire as to whether a student has any previous offences for academic malpractice as this will indicate the appropriate panel to refer a case to. This information is usually retained in the student’s School record. This will assist the AUO in determining whether a case can be heard by a Summary Disciplinary Panel (“SDP”) or if the case should be referred to the University Disciplinary Panel (“UDP”).
Section 5 Case handling, Paragraph 5.1, Page 10; Extracted text SHA256 db1ed4db97896ef1f771a937943e2402de1a954b0b0a56c53a781efa68c9af77; original binding lines 553–560; characters 35279–35978; excerpt offset 0–699
Official university source ↗
5.4. The original person who reported the alleged malpractice should not be a member of the disciplinary panel. Additionally, where a student has already been interviewed or attended a viva as part of the information gathering exercise, any future disciplinary panel should not include, as a member of the panel, the same examiner or School Officer.
Section 5 Case handling, Paragraph 5.4, Page 11; Extracted text SHA256 db1ed4db97896ef1f771a937943e2402de1a954b0b0a56c53a781efa68c9af77; original binding lines 617–620; characters 40035–40411; excerpt offset 0–376
Official university source ↗

AI use questioned?Investigation, possible outcomes and appeal

AI tools & access

Microsoft CopilotInstitutional access / licenceRecorded as allowed in the source scope
Log in to copilot.microsoft.com or Microsoft Teams using University credentials.
Microsoft Copilot · Access conditions
Enterprise GenAI conversational assistant (Copilot Chat) available to everyone with a University IT account, backed by Commercial Data Protection.
Log in to copilot.microsoft.com or Microsoft Teams using University credentials.
Free to university account holders
Microsoft Copilot · Official evidence
Source 1 ↗
Original quotation
Copilot Chat is an AI-powered assistant available to everyone with a University account and accessible via a web browser or within Microsoft Teams.
Source 2 ↗
Original quotation
Sometimes Copilot Chat may search the web using Microsoft’s search engine Bing in order to find information that is relevant to your prompt. When this occurs, fragments of your prompt may be sent to Bing. There is no way to prevent this from happening, however your identity is not shared, and the query is sent over a secure connection.
Microsoft 365 CopilotInstitutional access / licenceConditions apply
Licenses assigned in phased cohorts; check the Microsoft 365 Copilot SharePoint space.
Microsoft 365 Copilot · Access conditions
Microsoft 365 Copilot suite in phased license rollout across 65,000 colleagues and students; exclusive service permitted for staff handling student-identifiable data in teaching and learning (DocID 79331 §2.3.1).
Licenses assigned in phased cohorts; check the Microsoft 365 Copilot SharePoint space.
Provided under University enterprise agreement; phased allocation
Microsoft 365 Copilot · Official evidence
Source 1 ↗
Original quotation
The University has announced a strategic collaboration with Microsoft, making Manchester the world’s first university to deploy equitable Microsoft 365 Copilot access and training across its entire community.
Source 2 ↗
Original quotation
The roll out of licenses will be phased and implementation planning is now underway. Visit the Microsoft 365 Copilot SharePoint space for guidance, FAQs, training and updates as the roll out continues.
Source 3 ↗
Original quotation
2.3.1 Staff members who use AI in Teaching and Learning activities must adhere to the University's AI Guidelines. Only the University-provided Microsoft 365 Copilot service may be used for student-identifiable or confidential data.
NebulaONEUniversity-hosted serviceConditions apply
Submit early access request via the Nebula One Request Form.
NebulaONE · Access conditions
AI toolbox built within UoM's cloud environment for creating custom AI agents and safe experimentation.
Submit early access request via the Nebula One Request Form.
University-funded cloud environment
NebulaONE · Official evidence
Source 1 ↗
Original quotation
NebulaONE is an AI toolbox built within UoM’s cloud environment. It uses market-leading models to help you create custom AI agents, no coding required. Whether you're in research, teaching, or professional services, NebulaONE enables safe experimentation while ensuring full compliance with the University’s AI Guidelines.
Source 2 ↗
Original quotation
We have recently started onboarding early adopters to test the NebulaONE AI system. If you’re interested in gaining early access, please sign up using the Nebula One Request Form.

Record updatesLast 90 days · Recorded updates: 3

Updates to this site's reviewed record, not confirmation that the university changed its policy.

2026-10-27Page update
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2026-10-22Record maintenance
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2026-10-22Record addition · Site correction
Academic integrity · Teaching · 3 more topics · Records involved: 31 (15 corrected / adjusted · 16 added)
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Reviewed claims

31

Official sources

8 official URLs; 8 source attributions and their captured versions retained.

AI in Teaching and Learning Policy

documents.manchester.ac.uk

University official source

Senate, The University of Manchester

Hash and captured version

AI in Teaching and Learning Policy · 2026-10-21T15:06:00Z

SHA-256 of the retained capture file bytes.

dcff27c5977597bc51e7617581945974a44729b229de2e9efe42e230d00ccaeb

Hashes identify a captured version; they do not establish current policy or review approval.

Official source ↗

Academic Malpractice Procedure

documents.manchester.ac.uk

University official source

Student and Academic Services, The University of Manchester

Hash and captured version

Academic Malpractice Procedure · 2026-10-21T15:06:00Z

SHA-256 of the retained capture file bytes.

23a15e2b813deead551a3e3151c3b3f01a17d7c204723f94abd4c76494b31e49

Hashes identify a captured version; they do not establish current policy or review approval.

Official source ↗

University AI Guidelines | AI Hub | StaffNet | The University of Manchester

www.staffnet.manchester.ac.uk

University official source

StaffNet, The University of Manchester

Hash and captured version

University AI Guidelines | AI Hub | StaffNet | The University of Manchester · 2026-10-21T15:06:00Z

SHA-256 of the retained capture file bytes.

becd22deed500c75cb396085f5e2023181214ce41ca020584032407b014db270

Hashes identify a captured version; they do not establish current policy or review approval.

Official source ↗

Approved Tools | AI Hub | StaffNet | The University of Manchester

www.staffnet.manchester.ac.uk

University official source

StaffNet, The University of Manchester

Hash and captured version

Approved Tools | AI Hub | StaffNet | The University of Manchester · 2026-10-21T15:06:00Z

SHA-256 of the retained capture file bytes.

308d1a6ab33417437cf2580a3f79c6e6b0c1c1687d1531dd6de9a86970b8b398

Hashes identify a captured version; they do not establish current policy or review approval.

Official source ↗

AI and referencing - Referencing guide at the University of Manchester

subjects.library.manchester.ac.uk

University official source

University of Manchester Library

Hash and captured version

AI and referencing - Referencing guide at the University of Manchester · 2026-10-21T15:06:00Z

SHA-256 of the retained capture file bytes.

7a92ceddd3973ac5742b594cd7454424eac321a4469555ae8c15f89b86505d65

Hashes identify a captured version; they do not establish current policy or review approval.

Official source ↗

Copilot (The University of Manchester)

www.itservices.manchester.ac.uk

University official source

IT Services, The University of Manchester

Hash and captured version

Copilot (The University of Manchester) · 2026-10-21T15:06:00Z

SHA-256 of the retained capture file bytes.

f4482920cb6906f1bc0db2421c6c757cd3618c63cadcd40b7087bd7454913881

Hashes identify a captured version; they do not establish current policy or review approval.

Official source ↗

Artificial Intelligence and Teaching and Learning - Teaching College

www.teachingcollege.fse.manchester.ac.uk

University official source

Faculty of Science and Engineering Teaching College, The University of Manchester

Hash and captured version

Artificial Intelligence and Teaching and Learning - Teaching College · 2026-10-21T15:06:00Z

SHA-256 of the retained capture file bytes.

fce26e2c6bb6df07090689b87c4222118190a262f5d5dbaf73d1c98e0d785b7f

Hashes identify a captured version; they do not establish current policy or review approval.

Official source ↗

AI Guidance for Learners - Technology Enhanced Learning and Design

elearning.bmh.manchester.ac.uk

University official source

Faculty of Biology, Medicine and Health, The University of Manchester

Hash and captured version

AI Guidance for Learners - Technology Enhanced Learning and Design · 2026-10-21T15:06:00Z

SHA-256 of the retained capture file bytes.

ee497397a173ad2529eb76ec25b69eb24ba2f9e90c85dcce2aafbcf83b949e00

Hashes identify a captured version; they do not establish current policy or review approval.

Official source ↗

Record information, JSON & citation

Review layers: claim review applies to the claims only. Analysis is a separate machine-generated summary awaiting review. Coverage scores do not establish complete policy knowledge.

Claim review state: agent_reviewed
Analysis review state: machine_candidate
Record revision: qs35-40-v6-r4-meta-20261022
Dataset release: public-release-20260924-002
Correction published: 2026-10-22T15:59:18.511995Z
Student snapshot: Not published

Current reviewed JSON · Historical baseline

Published V6 presentation; JSON and MCP retain the existing public record. Supplementary quotations and scope notes remain pending review. Local candidate corrections, tools and student summaries are not approved for publication. Institution-wide audit remains PARTIAL.

No separate centralized AI examination policy document exists; exams are categorized individually under the Senate 4-category framework (DocID 79331 §2.1.1).
Public REST API tools.json exposes 8 standalone records for universitySlug=='manchester' without explicit id fields; reconciled by naturalKey into 3 canonical tool proposals. MCP get_student_policy returns an empty tool array.
DocID 639 references separate University instruments—Regulation XVII (Conduct and Discipline of Students), Guidance to students on Penalties for Academic Malpractice, and SDP/UDP procedures—which are not captured in the current source bundle; specific appeal deadlines, start events, and penalty tariffs are held.
Complete private historical held decisions have not been independently reconciled; original captured history is preserved.
The historical student snapshot is preserved and does not grant approval to this local corrected view.

Current reviewed JSON

Questions students ask

Questions students ask

Can I use AI for my coursework?

Under Senate Policy DocID 79331 §2.1.1, assessments are categorized into four levels (Category A: AI Prohibited, Category B: AI Minimal, Category C: AI Permitted, Category D: AI-Integrated) by Course Unit Directors and clearly stated in unit specifications and Canvas briefs (§2.1.3). Students may choose not to use AI for Categories A, B, and C without disadvantage, but this choice does not apply to Category D assessments which assess AI learning outcomes (§2.1.2). In Category A, all AI use including proofreading and text editing is prohibited; in Category B, AI is restricted to presentation only (fluency, grammar, spelling, formatting) without altering student ideas, arguments, or conclusions.

View evidence →

Do I need to disclose AI use?

Under University Library referencing guidance, students must cite generative AI tools when using text or images directly in their work following 'Cite them Right' conventions. Where asked or deemed appropriate, students should include an overview acknowledgement at the start of work or in a footnote. An appendix detailing relevant prompts, outputs, generation dates, and modification statements is required when referencing AI as personal communication or when instructed by School guidance. Using tools for basic grammar and spell checking does not require acknowledgement unless School guidance requires it.

View evidence →

Can I upload sensitive data?

Under Senate Policy DocID 79331 §2.2.1(c), students must not upload University-owned copyright materials (such as lecture recordings, slides, handouts, or examination questions) to external commercial AI tools. Under §2.2.2, students are explicitly permitted to upload session recordings into University-provided Microsoft 365 Copilot for study support. Under §2.3.1, staff members who use AI in Teaching and Learning activities must adhere to the University's AI Guidelines, and only the University-provided Microsoft 365 Copilot service may be used for student-identifiable or confidential data.

View evidence →

Which tools can I access?

The University provides Microsoft Copilot Chat with Commercial Data Protection to all active students and staff using University credentials. Microsoft 365 Copilot suite is deploying in phased license cohorts across 65,000 colleagues and students. NebulaONE is provided as an enterprise cloud AI development sandbox. Under DocID 79331 §2.1.1 and §2.2.1, having access to institutional AI tools does not confer permission to use them in Category A assessments.

View evidence →

What are the examination rules?

Examinations and timed assessments are categorized individually under the four-category framework (DocID 79331 §2.1.1). Under Academic Malpractice Procedure DocID 639 §3.1.2.5 and §4.3.1, students must adhere strictly to examination conditions communicated before the exam, and possessing or using unauthorized AI tools or online materials in examination sittings constitutes academic malpractice.

View evidence →

What rules apply to research and publication?

Under StaffNet Research Guidelines, any use of AI to synthesise research data must be completely transparent, and fabricating or falsifying data with AI constitutes research misconduct. Corresponding authors carry ultimate responsibility for publication credibility and must declare significant AI assistance. Researchers reviewing papers or grants must preserve peer review confidentiality and never upload unpublished manuscripts into external AI services.

View evidence →

What counts as academic misconduct?

The University does not currently use software claiming to detect generative AI; Turnitin alone does not confirm malpractice and academic judgment is required. Under Academic Malpractice Procedure DocID 639 §4.4.2, where indicators raise concerns of commissioned work without direct evidence, or available information does not satisfy the balance of probabilities, a viva voce can be arranged in agreement with the School Officer to demonstrate authorship; it does not contribute to the mark. If held, it should not normally take place more than 30 working days after the assessment feedback deadline (§4.4.3.1); the student should receive at least five working days notice explaining its nature, purpose and potential outcomes (§4.4.3.2). Accompaniment by a person of the student’s choice is for support only without participation (§4.4.3.4), and reasonable adjustments must be made (§4.4.3.5). The viva itself cannot impose a penalty (§4.4.4.2); case handling follows the applicable AUO/SDP/UDP procedures (§5.1–5.5).

View evidence →

What guidance applies to teaching?

Senate Policy DocID 79331 and Faculty guidance mandate that Course Unit Directors specify AI categories in unit specifications and Canvas briefs (§2.1.3), establish group work logging rules and require prior peer consent before recording group discussions (§2.1.4–2.1.5), and require teaching staff handling student-identifiable data to use M365 Copilot (§2.3.1). Faculty guidance (FSE, BMH) supplements central policy.

View evidence →

What security and procurement requirements apply?

IT Services and Information Governance establish clear tenant boundaries for Copilot Chat, Microsoft 365 Copilot, and NebulaONE cloud sandbox, ensuring user authentication, commercial data encryption, and exclusion of university data from public LLM training.

View evidence →

When was this record checked?

Record checked: 2026-10-21

Record version →

Which official sources support these rules?

Official source →

Where can I read the full evidence?

31 · Full policy evidence

Full policy evidence →

The University of Manchester AI Policy