Montpellier, France

Université de Montpellier

Last checkedMay 16, 2026Last changedMay 16, 2026Review: Agent reviewedConfidence95%

Public JSON Change log Monthly report Citation rules Dataset access Analysis JSON Submit correction

Policy statusReviewed evidence-backed recordReview: Agent reviewedClaim coverage6 reviewedEvidence-backed claims6Reviewed6Candidate0Official sources3Source languagefrPublic JSON/api/public/v1/universities/universite-de-montpellier.json

Coverage score85/100Coverage labelbroad public coverageReview: Machine candidateAnalysis confidence77%

Policy presence

Université de Montpellier has 5 source-backed public claims for policy presence; deterministic analysis status: unclear.

UnclearMachine candidateConfidence78%Evidence5Sources2

Claim claim-um-privacy-001 Claim claim-um-academic-integrity-001 Claim claim-um-teaching-001

AI disclosure

No source-backed public claim about AI disclosure or acknowledgement is present in this profile.

The current public tracker record does not contain claim evidence about disclosing, acknowledging, citing, or declaring AI use.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Coursework

Université de Montpellier has 4 source-backed public claims for coursework; deterministic analysis status: recommended.

RecommendedMachine candidateConfidence76%Evidence4Sources3

Claim claim-um-academic-integrity-001 Claim claim-um-teaching-001 Claim claim-um-ai-tool-treatment-001

Exams

Université de Montpellier has 4 source-backed public claims for exams; deterministic analysis status: recommended.

RecommendedMachine candidateConfidence76%Evidence4Sources3

Claim claim-um-academic-integrity-001 Claim claim-um-teaching-001 Claim claim-um-ai-tool-treatment-001

Privacy and data entry

Université de Montpellier has 1 source-backed public claim for privacy and data entry; deterministic analysis status: restricted.

RestrictedMachine candidateConfidence81%Evidence1Sources1

Claim claim-um-privacy-001

Academic integrity

Université de Montpellier has 1 source-backed public claim for academic integrity; deterministic analysis status: recommended.

RecommendedMachine candidateConfidence79%Evidence1Sources1

Claim claim-um-academic-integrity-001

Approved tools

Université de Montpellier has 1 source-backed public claim for approved tools; deterministic analysis status: recommended.

RecommendedMachine candidateConfidence75%Evidence1Sources1

Claim claim-um-ai-tool-treatment-001

Named AI services

Université de Montpellier has 2 source-backed public claims for named ai services; deterministic analysis status: restricted.

RestrictedMachine candidateConfidence78%Evidence2Sources2

Claim claim-um-privacy-001 Claim claim-um-ai-tool-treatment-001

Teaching guidance

Université de Montpellier has 3 source-backed public claims for teaching guidance; deterministic analysis status: recommended.

RecommendedMachine candidateConfidence76%Evidence3Sources2

Claim claim-um-academic-integrity-001 Claim claim-um-teaching-001 Claim claim-um-teaching-002

Research guidance

Université de Montpellier has 1 source-backed public claim for research guidance; deterministic analysis status: recommended.

RecommendedMachine candidateConfidence71%Evidence1Sources1

Claim claim-um-teaching-002

Security and procurement

No source-backed public claim about AI security review or procurement is present in this profile.

The current public tracker record does not contain claim evidence about security review, procurement, vendor approval, risk assessment, authentication, SSO, or enterprise licensing.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Derived tool records1

Microsoft Copilot

Université de Montpellier

Tool: Microsoft Copilot
About: Not specified
Access: Not specified
Cost: Not specified
Availability: Unknown
Review: Agent reviewed
Sources: Source 1 Source 2 Source 3

Evidence-backed claims

6 reviewed evidence-backed public claim

Normalized value: no_nominative_confidential_sensitive_data_in_public_ai_tool

Last checked: May 16, 2026
Last changed: May 16, 2026

Original evidence

Evidence 1

Le respect de la confidentialite et de la vie privee, ainsi que la protection des donnees personnelles et de la propriete intellectuelle, doivent toujours etre garantis. Aucune donnee nominative, confidentielle ou sensible ne doit etre utilisee dans un outil d'IA public.
Source: Principes pour l'usage de l'IA dans la formation a l'Universite de Montpellier

Localized display only

The source says confidentiality, privacy, personal data, and IP protections should be guaranteed, and no nominative, confidential, or sensitive data should be used in a public AI tool.

Source language: Francais (fr)
Snapshot hash: 268d1366e75f66a7c22e885cd1cc4811a033b0e464768b69f159cd323626afcc
Retrieved: May 16, 2026
Evidence locator: Principe 5, section 5.2

Normalized value: students_follow_regulations_course_rules_assessment_instructions

Last checked: May 16, 2026
Last changed: May 16, 2026

Original evidence

Evidence 1

L'utilisation de l'IA par les etudiantes et etudiants doit respecter les reglements en vigueur a l'Universite de Montpellier, les regles propres a chaque enseignement et les consignes specifiques a chaque evaluation. Les attentes concernant l'utilisation de l'IA sont explicitees dans les programmes de cours et expliquees aux etudiantes et etudiants.
Source: Principes pour l'usage de l'IA dans la formation a l'Universite de Montpellier

Localized display only

The source says student AI use should respect UM regulations, teaching-specific rules, and assessment instructions; expectations should be explained in courses.

Source language: Francais (fr)
Snapshot hash: 268d1366e75f66a7c22e885cd1cc4811a033b0e464768b69f159cd323626afcc
Retrieved: May 16, 2026
Evidence locator: Principe 6, sections 6.2 and 6.3

Normalized value: teacher_decision_learning_objectives

Last checked: May 16, 2026
Last changed: May 16, 2026

Original evidence

Evidence 1

La decision d'utiliser ou d'aborder l'IA dans les activites de formation releve des personnels enseignants, et s'appuie sur une exploration des possibilites que l'IA offre dans leur domaine disciplinaire, en coherence avec les objectifs d'apprentissage.
Source: Principes pour l'usage de l'IA dans la formation a l'Universite de Montpellier

Localized display only

The source says decisions to use or address AI in training activities belong to teaching staff and should align with learning objectives.

Source language: Francais (fr)
Snapshot hash: 268d1366e75f66a7c22e885cd1cc4811a033b0e464768b69f159cd323626afcc
Retrieved: May 16, 2026
Evidence locator: Principe 2, section 2.1

Normalized value: official_ai_training_principles_found_no_separate_central_binding_ai_policy

Last checked: May 16, 2026
Last changed: May 16, 2026

Original evidence

Evidence 1

Face aux enjeux lies a l'essor de l'IA, l'Universite de Montpellier a defini 7 principes pour l'usage de l'intelligence artificielle dans la formation. Ils ont ete votes par la Commission Formation et Vie Universitaire du 28 janvier 2025 et presentes au Conseil d'Administration du 3 fevrier 2025.
Source: Principes pour l'usage de l'IA dans la formation a l'Universite de Montpellier

Localized display only

UM says it defined seven AI-in-training principles, voted by CFVU on 2025-01-28 and presented to the board on 2025-02-03.

Source language: Francais (fr)
Snapshot hash: 268d1366e75f66a7c22e885cd1cc4811a033b0e464768b69f159cd323626afcc
Retrieved: May 16, 2026
Evidence locator: Introductory note above Preambule

Normalized value: institutional_copilot_access_a1_a3_staff_students_data_protection

Last checked: May 16, 2026
Last changed: May 16, 2026

Original evidence

Evidence 1

L'Universite de Montpellier a un acces institutionnel a Copilot avec les licences A1 et A3 mises a disposition des personnels et etudiants. Cela signifie que vous beneficiez d'avantages, comme celui de la protection de vos donnees.
Source: Utiliser Copilot avec votre compte institutionnel UM

Localized display only

UM says it has institutional Copilot access through A1/A3 licences for staff and students, with advantages such as data protection.

Source language: Francais (fr)
Snapshot hash: cfd6ea215023e1786b8a774f86331e7d574b8cc1f1110054221591badb808843
Retrieved: May 16, 2026
Evidence locator: Main article body

Normalized value: ai_hub_training_resources_for_community

Last checked: May 16, 2026
Last changed: May 16, 2026

Original evidence

Evidence 1

Cet espace propose plusieurs parcours pour accompagner enseignants, chercheurs, personnels et etudiants dans la decouverte et l'appropriation des usages de l'IA. Contenu disponible : Outils & plateformes IA; Ressources & replays; Formations en autoformation; Acculturation des etudiants.
Source: Intelligence Artificielle

Localized display only

The UM AI hub says it offers multiple pathways and resources for teachers, researchers, staff, and students.

Source language: Francais (fr)
Snapshot hash: 81283164d51764003a33f2d5d9996822c790e87b5a9771195647cbc1fc7008d8
Retrieved: May 16, 2026
Evidence locator: Outils, formations et ressources a l'UM

Candidate claims

0 machine or needs-review claim

Official sources

3 source attribution

Intelligence Artificielle

numerique.umontpellier.fr

Source URL: https://numerique.umontpellier.fr/intelligence-artificielle/
Snapshot hash: 81283164d51764003a33f2d5d9996822c790e87b5a9771195647cbc1fc7008d8

Principes pour l'usage de l'IA dans la formation a l'Universite de Montpellier

numerique.umontpellier.fr

Source URL: https://numerique.umontpellier.fr/intelligence-artificielle/principes-ia-formation/
Snapshot hash: 268d1366e75f66a7c22e885cd1cc4811a033b0e464768b69f159cd323626afcc

Utiliser Copilot avec votre compte institutionnel UM

numerique.umontpellier.fr

Source URL: https://numerique.umontpellier.fr/utiliser-copilot-avec-votre-compte-institutionnel-um/
Snapshot hash: cfd6ea215023e1786b8a774f86331e7d574b8cc1f1110054221591badb808843

Last checkedMay 16, 2026Last changedMay 16, 2026Open change log

Open contribution paths Review workflow

Back to universities

Université de Montpellier

Record status

Policy profile

Policy presence

AI disclosure

Coursework

Exams

Privacy and data entry

Academic integrity

Approved tools

Named AI services

Teaching guidance

Research guidance

Security and procurement

AI tools

Microsoft Copilot

Evidence-backed claims

UM's AI-in-training principles say confidentiality, privacy, personal data, and intellectual property protections should be guaranteed, and no nominative, confidential, or sensitive data should be used in a public AI tool.

UM's AI-in-training principles say student AI use should respect university regulations, rules for each teaching activity, and assessment-specific instructions; expectations should be clarified in course and assessment materials.

UM's AI-in-training principles say decisions to use or address AI in training activities rest with teaching staff and should align with learning objectives.

Universite de Montpellier has official AI-in-training principles, but this staged crawl found no separate central binding AI policy page.

UM's digital-services guidance says the university provides institutional Microsoft Copilot access through A1 and A3 licences for staff and students, with data-protection advantages.

UM's official AI hub says it offers multiple pathways to help teachers, researchers, staff, and students discover and appropriate AI uses, including AI tools/platforms, resources, self-training, and student acculturation.

Candidate claims

Official sources

Intelligence Artificielle

Principes pour l'usage de l'IA dans la formation a l'Universite de Montpellier

Utiliser Copilot avec votre compte institutionnel UM

Change log

Corrections