Policy presence
Texas A&M University has 5 source-backed public claims for policy presence; deterministic analysis status: unclear.
College Station, United States
Texas A&M University
Record status
Review: Agent reviewed
Policy profile
Review: Machine candidate
AI disclosure
Texas A&M University has 2 source-backed public claims for ai disclosure; deterministic analysis status: required.
Coursework
Texas A&M University has 5 source-backed public claims for coursework; deterministic analysis status: restricted.
Exams
Texas A&M University has 5 source-backed public claims for exams; deterministic analysis status: restricted.
Privacy and data entry
Texas A&M University has 4 source-backed public claims for privacy and data entry; deterministic analysis status: restricted.
Academic integrity
Texas A&M University has 3 source-backed public claims for academic integrity; deterministic analysis status: required.
Approved tools
Texas A&M University has 4 source-backed public claims for approved tools; deterministic analysis status: restricted.
Named AI services
Texas A&M University has 4 source-backed public claims for named ai services; deterministic analysis status: restricted.
Teaching guidance
Texas A&M University has 3 source-backed public claims for teaching guidance; deterministic analysis status: recommended.
Research guidance
Texas A&M University has 2 source-backed public claims for research guidance; deterministic analysis status: recommended.
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.
AI tools
Evidence-backed claims
9 reviewed evidence-backed public claim
Privacy
Texas A&M guidance says everyone must follow data privacy and security guidelines when using generative AI to protect personal and institutional data.
Review: Agent reviewed
Normalized value: AI users must follow data privacy and security guidance
Original evidence
Evidence 1Everyone must follow data privacy and security guidelines when using generative AI, protecting personal and institutional data.
Localized display only
The source uses mandatory language for data privacy and security guidance.
Source Status
Texas A&M publishes official recommendations and guidance for responsible generative AI use at the university, scoped to benefits and risks including academic integrity, privacy, and ethical use considerations.
Review: Agent reviewed
Normalized value: Responsible AI guidance page exists
Original evidence
Evidence 1The purpose of this page is to provide recommendations and guidance on the responsible use of generative AI at Texas A&M University, ensuring its potential benefits are maximized while minimizing risks to academic integrity, privacy and other ethical use considerations.
Localized display only
Texas A&M frames this page as responsible-use guidance, not as a standalone formal policy.
Academic Integrity
Texas A&M strongly advises against sole reliance on AI detection tools because of limitations including inaccuracy, bias, ease of circumvention, and rapid AI evolution.
Review: Agent reviewed
Normalized value: Caution against sole reliance on AI detection tools
Original evidence
Evidence 1Although AI detection tools are available, the university strongly advises against sole reliance on these tools due to the following limitations: Inaccuracy, Bias, Ease of Circumvention, Rapid Evolution of AI.
Localized display only
The page recommends caution and a broader integrity approach rather than sole detector use.
Ai Tool Treatment
Texas A&M Technology Services describes TAMU AI Chat as a secure, university-approved platform open to all students and employees, with support for content classified as University-Confidential or lower.
Review: Agent reviewed
Normalized value: TAMU AI Chat approved for students and employees with University-Confidential-or-lower support
Original evidence
Evidence 1Open to all Texas A&M students and employees, TAMU AI Chat (currently in BETA) provides staff, faculty, researchers, and students with a secure, university-approved platform to access multiple AI tools like OpenAI's GPT, Anthropic's Claude Sonnet, and Google's Gemini. TAMU AI Chat supports content classified as University-Confidential or lower.
Localized display only
The service page names TAMU AI Chat as university-approved and gives the supported data classification.
Privacy
Texas A&M Technology Services says Google and Microsoft AI tools are approved for University-Confidential-or-lower data, but should not be used with export-controlled data, government ID numbers, or financial records.
Review: Agent reviewed
Normalized value: Google and Microsoft AI tools have data restrictions
Original evidence
Evidence 1Google and Microsoft tools are approved for data classified as University-Confidential or lower, and should not be used with export-controlled data, government ID numbers, or financial records.
Localized display only
The page allows these tools for a stated data classification and excludes specific sensitive categories.
Academic Integrity
Texas A&M guidance says generative AI users must acknowledge nontrivial AI-generated content and avoid plagiarism, while faculty should provide clear course instructions about permissible AI uses.
Review: Agent reviewed
Normalized value: AI disclosure and course guidance tied to academic integrity
Original evidence
Evidence 1When using generative AI, users must acknowledge the use of nontrivial AI-generated content and avoid plagiarism. This includes properly citing AI-generated content in academic work and ensuring that AI-generated content does not violate academic integrity policies. The faculty should provide clear instructions about permissible AI uses in their courses.
Localized display only
The source combines user acknowledgment obligations with instructor course guidance.
Ai Tool Treatment
Texas A&M presents AI Use Categories as a starting point for student-instructor conversation, not as a one-size-fits-all policy or replacement for instructor judgment.
Review: Agent reviewed
Normalized value: Course AI-use categories are guidance, not universal policy
Original evidence
Evidence 1The AI Use Categories give students and instructors a starting point for conversation about AI usage in a course. While these categories are not a one-size-fits-all policy, nor are they meant to replace instructor judgment, they offer a shared way to think about different types of AI use.
Localized display only
The page explicitly avoids treating the AI categories as a universal policy.
Research
Texas A&M Division of Research says its Best Practices for Generative AI in Research document should serve as a researcher resource and framework for colleges or schools to develop specific action plans.
Review: Agent reviewed
Normalized value: Research AI best-practices document is a resource and framework
Original evidence
Evidence 1This document should serve as a resource for researchers and provide a framework for each college or school to develop detailed and specific action plans tailored to their unique and specialized needs.
Localized display only
The memo frames the research document as a resource and framework rather than a final college-level action plan.
Teaching
Texas A&M CTE syllabus guidance recommends a hybrid approach that establishes clear course or assignment expectations for generative AI use, reinforces that AI use in coursework is governed by the Aggie Honor Code, and provides faculty support guidance.
Review: Agent reviewed
Normalized value: Recommended hybrid syllabus approach for generative AI
Original evidence
Evidence 13. (Recommended) Pursue a hybrid of the two previous options, including both of the following: a. An addition to the minimum syllabus requirements, which both i. makes explicit the responsibility of instructors and students to establish clear expectations for generative AI use within each course and/or assignment and ii. reinforces that the use of generative AI in academic coursework is integrally related to academic integrity and will be governed by the Aggie Honor Code. b. Guidance provided to support faculty in making their individual determinations.
Localized display only
The PDF recommends a hybrid syllabus approach and ties coursework AI use to academic integrity and the Aggie Honor Code.
Candidate claims
0 machine or needs-review claim
Official sources
6 source attribution
AI Detection Tools | Artificial Intelligence
ai.tamu.edu
AI Services | Technology Services
it.tamu.edu
Best Practices for Generative AI in Research
research.tamu.edu
Generative AI Syllabus Statement Considerations
ai.tamu.edu
Learn With AI | Artificial Intelligence
ai.tamu.edu
Use Guidelines and Ethics | Artificial Intelligence
ai.tamu.edu