Policy presence
University of Milan has 1 source-backed public claim for policy presence; deterministic analysis status: unclear.
Milan, Italy
University of Milan
University of Milan is listed as QS 2026 rank =276. University of Milan has 6 source-backed AI policy claim records from 4 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.
Short answer
v1 public contract
University of Milan is listed as QS 2026 rank =276. University of Milan has 6 source-backed AI policy claim records from 4 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.
Citation-ready summary
As of this public record, University AI Policy Tracker lists University of Milan as an agent-reviewed AI policy record last checked on May 16, 2026 and last changed on May 16, 2026. The record contains 6 source-backed claims, including 6 reviewed claims, from 4 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/university-of-milan.json. The entity-level confidence is 93%. This tracker is not legal advice, not academic integrity advice, and not an official university statement unless the linked source is the university's own official page.
Policy signals in this record
- Evidence includes Teaching claims.
- Evidence includes Academic integrity claims.
- Evidence includes Research claims.
- Evidence includes AI tool treatment claims.
- Evidence includes Privacy claims.
- Evidence includes Procurement claims.
- No specific AI service name is highlighted by the current public claim text.
- Teaching, assessment, coursework, or syllabus-related language appears in the public claim text.
Review: Agent reviewed
This reference record summarizes visible public data only. Official sources and original-language evidence remain canonical; confidence is separate from review state.
This page is not legal advice, not academic integrity advice, and not an official university statement unless a linked source is the university's own official page.
Policy profile
Deterministic source-backed dimensions derived from this record's public claims.
Review: Machine candidate
Policy profile rows are machine-candidate derived metadata. They are not final policy conclusions; inspect the linked claim evidence before reuse.
Analysis page-quality metadata is available at /api/public/v1/analysis/page-quality.json.
AI disclosure
University of Milan has 2 source-backed public claims for ai disclosure; deterministic analysis status: required.
Coursework
University of Milan has 2 source-backed public claims for coursework; deterministic analysis status: required.
Exams
University of Milan has 3 source-backed public claims for exams; deterministic analysis status: required.
Privacy and data entry
University of Milan has 2 source-backed public claims for privacy and data entry; deterministic analysis status: restricted.
Academic integrity
University of Milan has 1 source-backed public claim for academic integrity; deterministic analysis status: required.
Approved tools
University of Milan has 2 source-backed public claims for approved tools; deterministic analysis status: allowed.
Named AI services
University of Milan has 3 source-backed public claims for named ai services; deterministic analysis status: restricted.
Teaching guidance
University of Milan has 3 source-backed public claims for teaching guidance; deterministic analysis status: recommended.
Research guidance
University of Milan has 3 source-backed public claims for research guidance; deterministic analysis status: restricted.
Security and procurement
University of Milan has 1 source-backed public claim for security and procurement; deterministic analysis status: required.
Coverage score measures breadth of public, source-backed coverage only. It is not a policy quality, strictness, legal adequacy, safety, or compliance score.
Evidence-backed claims
6 reviewed evidence-backed public claim
Teaching
For educational activities, the University of Milan permits AI-supported self-assessment when explicit, but does not permit delegating learning assessment to AI tools when the assessment contributes to the final exam grade.
Review: Agent reviewed
Normalized value: no_ai_delegation_for_final_grade_assessment
Original evidence
Evidence 1It is never permitted to delegate any learning assessment activity to AI tools when such activity involves an assessment that contributes to the final exam grade. Self-assessment aimed at improving learning is instead permitted and promoted provided it is made explicit in the tools and methods of use.
Academic Integrity
In educational settings, the University of Milan advises that students must explicitly declare AI use in assessed work and that teachers must explicitly declare AI use in educational activities.
Review: Agent reviewed
Normalized value: declare_ai_use_in_teaching_and_assessed_work
Original evidence
Evidence 1For teachers: any use of AI tools in educational activities must be made explicit and declared, both regarding the specific tool used and the methods of use. For students: any use of AI tools in producing work subject to assessment must be made explicit and declared, specifying the methods of use and purposes.
Research
For research, the University of Milan advises research staff to use AI while respecting responsibility, transparency, and respect, and says researchers remain fully responsible for results produced with AI tools.
Review: Agent reviewed
Normalized value: research_ai_responsibility_transparency_respect
Original evidence
Evidence 1This is why the University advises its research staff to learn about, exploit, and systematically implement the best existing tools while, at the same time, urging them to always do so while respecting three fundamental principles that must characterize the entire process of using these tools: responsibility, transparency, and respect. Throughout the entire research process... the researcher... must at all times understand that they are fully responsible for all results produced by the tools used, regardless of AI use or not.
Ai Tool Treatment
The University of Milan has an AI governance document intended to promote ethical, legally compliant and conscious use of AI tools, with annexed guidelines for teaching, research, third mission and administrative activities.
Review: Agent reviewed
Normalized value: ai_governance_guidelines
Original evidence
Evidence 1The goal of the document "Governing Artificial Intelligence within the University" is to promote an ethical, legally-compliant and conscious use of AI tools, by implementing the latest regulatory provisions on the subject, as well as best practices already adopted by many universities and research centres in Italy and abroad. The ten general principles stated in this document are accompanied by three Annexes containing specific guidelines for the use of AI in the areas of teaching, research and the third mission, and administrative activities.
Privacy
For AI use in research, the University of Milan guidance emphasizes data protection, operation traceability and regulatory compliance during AI-supported data analysis, and cautions against entering sensitive information into AI systems.
Review: Agent reviewed
Normalized value: research_ai_data_protection_traceability
Original evidence
Evidence 1In any case, data protection, operation traceability, and regulatory compliance must be guaranteed throughout the entire analysis process. The idea of respect then includes the need to correctly treat information entered into AI systems by respecting both privacy and data protection. Avoiding inserting particularly sensitive data into AI systems achieves both the objective of protecting the University's industrial secrets... and the rights and freedoms of people to whom any personal and sensitive data may refer.
Procurement
For administrative activities, the University of Milan says its AI adoption follows AGID public-administration guidelines and uses a methodology that considers AI Act compliance, data quality, personal data protection and cybersecurity requirements.
Review: Agent reviewed
Normalized value: administrative_ai_agid_methodology_requirements
Original evidence
Evidence 1As a public university, Universita degli Studi di Milano... promotes the adoption of AI tools in compliance with AGID guidelines for AI adoption in Public Administration. The following categories of requirements are particularly taken into consideration in the analysis phase: AI Act compliance; data management and quality; personal data protection; cybersecurity, in compliance with AGID guidelines.
Candidate claims
0 machine or needs-review claim
Candidate claims are not final policy conclusions. They preserve source URL, source snapshot hash, evidence, confidence, and review state so the record can be audited before review.
Official sources
4 source attribution
Governing AI within the University
unimi.it
Guidelines for Beneficial Use of AI in Administrative Activities
unimi.it
Guidelines for Beneficial Use of AI in Educational Settings
unimi.it
Guidelines for Beneficial Use of AI in Research
unimi.it
Change log
Source-check timeline and diff-style claim/evidence preview.
View the public change record for this university, including source snapshot hashes, claim review states, and a diff-style preview of current source-backed evidence.
Corrections and missing evidence
Corrections create review tasks and do not directly change this public record.
If an official source is missing, stale, moved, blocked, or incorrectly summarized, submit a source URL, policy change report, or institution correction for review. Corrections must preserve source URLs, source language, original evidence, review state, and audit history.