Elon University has defined AI policies across 10 of 12 policy categories, covering Academic Integrity, Institutional & Administrative, Research, Teaching & Learning. AI use in coursework is addressed on a case-by-case basis, with policies set at the instructor level. Students are required to disclose and attribute AI-generated content in their academic work. The university employs detection and enforcement mechanisms for unauthorized AI use. Research-related AI policies address data analysis, research ethics. At the institutional level, the university has established guidelines for faculty and staff AI use, data protection and approved AI tools, AI governance strategy.
The decision to incorporate these technologies into teaching and learning is at the discretion of the Elon faculty. While some faculty members may choose to utilize generative AI in their instruction in select instances, others may opt to refrain from its use. It is the responsibility of faculty to make their course policies clear and explicit and to discuss them openly with students. It is the responsibility of students to adhere to the guidelines established by their faculty.
Employing the output of these technologies in violation of the policy set by the faculty will be considered a violation of the academic integrity policies of the Elon University honor code.
The decision to incorporate these technologies into teaching and learning is at the discretion of the Elon faculty. While some faculty members may choose to utilize generative AI in their instruction in select instances, others may opt to refrain from its use. It is the responsibility of faculty to make their course policies clear and explicit and to discuss them openly with students. It is the responsibility of students to adhere to the guidelines established by their faculty.
Employing the output of these technologies in violation of the policy set by the faculty will be considered a violation of the academic integrity policies of the Elon University honor code.
* Does the permitted use of AI vary between learning activities and assessments?
The decision to incorporate these technologies into teaching and learning is at the discretion of the Elon faculty. While some faculty members may choose to utilize generative AI in their instruction in select instances, others may opt to refrain from its use. It is the responsibility of faculty to make their course policies clear and explicit and to discuss them openly with students. It is the responsibility of students to adhere to the guidelines established by their faculty.
Yes, you can bring your AI-enhanced writing to The Writing Center!
* Prior to your WC appointment, check with your professor or on the assignment sheet if AI-use is permitted.
The Writing Center hosts weekly Analog (AI-free) Drop-in Writing Sessions. Students are welcome to show up and get some writing done, meet with a consultant to discuss their drafts, or learn about AI-free strategies for brainstorming, organizing, revising, and proofreading.
* The use of AI in research must be done within the bounds of rigorous ethical standards. Researchers should take all necessary steps to understand the likely benefits of AI-enabled research, the limits that should be imposed on its application, and the risks (known and unknown) and potential negative consequences that might emerge from these technologies.
* The use of AI in research must be done within the bounds of rigorous ethical standards. Researchers should take all necessary steps to understand the likely benefits of AI-enabled research, the limits that should be imposed on its application, and the risks (known and unknown) and potential negative consequences that might emerge from these technologies.
* The use of AI is appropriate and effective in some applications and inappropriate and ineffective in others. Faculty should decide whether, when and how AI should be used in courses and clearly communicate those boundaries to students. Staff should incorporate the use of AI in their work with full awareness and support of their supervisors. In all situations intellectual honesty and transparency about the use of AI is paramount.
The continuum below provides a visualization of ways students may partner with AI in their learning, from the traditional fully learner-generated product to a completely AI created piece of work. To support students being successful in their learning and meeting the expectations of the Elon Honor Code , explicitly share with students what plagiarism and acceptable use (with and without attribution) looks like when engaging with AI in your course.
* What are ways that students might want to use AI in this course? What is the student’s responsibility for articulating their use of AI in their learning?
Please note, the use of AI in this course is optional. You are not required or expected to utilize AI to complete any course assignments. If you do utilize AI, please include a note on the assignment cover page which indicates how you utilized the tool. You are responsible for fact checking statements produced by AI language models.
3. Never present AI-generated content as their own. Consider the use of AI-generated tools as you would any other source that requires citation.
Employing the output of these technologies in violation of the policy set by the faculty will be considered a violation of the academic integrity policies of the Elon University honor code.
While AI detector software might seem useful as a way to check for or prevent unpermitted students’ AI-use, they are problematic, in many of the same ways plagiarism detector software is problematic, especially in an educational setting.
Failure to disclose AI use or improper use constitutes plagiarism and breaches academic integrity, leading to penalties such as a failing grade for the specific assignment.
The decision to incorporate these technologies into teaching and learning is at the discretion of the Elon faculty. While some faculty members may choose to utilize generative AI in their instruction in select instances, others may opt to refrain from its use. It is the responsibility of faculty to make their course policies clear and explicit and to discuss them openly with students.
* The use of AI is appropriate and effective in some applications and inappropriate and ineffective in others. Faculty should decide whether, when and how AI should be used in courses and clearly communicate those boundaries to students. Staff should incorporate the use of AI in their work with full awareness and support of their supervisors. In all situations intellectual honesty and transparency about the use of AI is paramount.
* AI systems used at Elon should never compromise the privacy of students’ personal information. While AI systems may be utilized, faculty and staff should maintain a primary role in the evaluation of students’ learning progress, behaviors and outcomes.
Information Technology faithfully stewards university data and technology systems, being attentive and cautious to protect users’ privacy and ensure the security of university data.
As you engage with AI tools, you must remain attentive to the kinds of data you are using, who owns that data, and the ethical responsibilities you have. With all the power of AI, this technology is immature, and it comes with increased usage risks.
Unless approved by Information Technology, no “Confidential data” should be used in AI applications.
* AI systems used at Elon should never compromise the privacy of students’ personal information.
Elon University AI Principles
* The use of AI at Elon should begin with the primacy of human health, well-being, dignity, safety, privacy and security.
* We see AI as a tool to enrich and enhance teaching, learning, creativity and human development. We believe the role of AI should be to augment, not fully replace the vital human relationships between teachers and learners, or within groups of peer learners.
* AI systems used at Elon should be transparent and neutral – they should disclose the positionality of their data and models and should not manipulate learning processes in unethical, deceptive or subliminal ways.
At Elon University, we are committed to using artificial intelligence (AI) to support and advance university operations in alignment with the University’s Generative AI Statement. AI holds immense potential for our daily work, and we are committed to deploying AI technologies in ways that support both effectiveness and efficiency. In doing so, we must recognize the importance of using AI responsibly and ethically within our administrative practices.
Knowing your institution's AI policy is step one. DocuMark helps enforce it fairly by empowering universities to manage AI-generated content, prevent cheating, and support student writing through responsible AI use.
Elon University has defined AI policies in 10 of 12 categories, with an overall coverage score of 83%.
Elon emphasizes transparency about AI use, but disclosure and citation expectations vary by instructor, course, and unit. Faculty are expected to state acceptable use boundaries, and some Elon materials require students to articulate or disclose AI use, while a School of Communications standard treats AI outputs like sources that require citation.
Elon states that using AI against faculty policy is an Honor Code violation. The Center for Writing Excellence also states that AI detectors are problematic in educational settings, and a School of Communications policy states that failure to disclose or improper AI use constitutes plagiarism and can lead to assignment-level penalties.
Elon requires users to protect privacy and university data when using AI tools. Confidential university data may not be used in AI applications unless Information Technology approves it, and the university states that AI systems used at Elon should never compromise students' personal information.
Disclaimer:* All university AI policy information presented on this platform is compiled from publicly available information, official university websites, and related academic sources. This data reflects information available at the time of last verification as on 27th February 2026. University and institution names referenced on this platform are the property and trademarks of their respective institutions. Their inclusion does not imply any affiliation with, endorsement by, or partnership with those institutions. Policy coverage scores and categorical indicators are automated assessments derived from available documentation and are provided for informational and comparative purposes only. They do not constitute legal, academic, or compliance advice. Users are advised to exercise their own judgement and independently verify all policy information directly with the respective university before making any academic or institutional decisions. For any queries or corrections, please contact us at support@trinka.ai