Regulatory Framework and Institutional Management for Adopting Large Language Models in Higher Education
DOI:
https://doi.org/10.20983/novarua.2026.32.1Keywords:
Large language models, Innovation management, Higher education, Institutional governance, Educational policyAbstract
The adoption of Large Language Models (LLM) in higher education offers opportunities for innovation, but also poses challenges with governance, regulation, and institutional accountability. Universities must balance ethical experimentation, academic integrity, and regulatory compliance; however, they lack consolidated frameworks for their responsible adoption. This study examines how these institutions are responding, through an analysis of regulatory and governance approaches to integrating LLMs, combining Systematic Literature Review (SLR) with a qualitative case study of Mexican higher education. This paper synthesizes evidence on regulatory frameworks, governance models, leadership strategies, and organizational change mechanisms for adopting generative artificial intelligence in universities. It finds how institutional policies and administrative practices emerge under conditions of regulatory uncertainty. Despite institutional interest in LLMs, governance responses remain fragmented, with tensions between innovation and regulation, regarding academic integrity, ethics, and implementation capacity.
References
Abhishek, A., Erickson, L., & Bandopadhyay, T. (2025). Data and AI governance: Promoting equity, ethics, and fairness in large language models (Versión 1). arXiv. https://doi.org/10.48550/ARXIV.2508.03970.
Abunaser, F. M., Hamd, M. M. M., Bani-Oraba, A. M. N., Hamed, O., Alshiyab, M. Q. M., & Shebani, Z. (2025). Dynamic Capabilities of University Administration and Their Impact on Student Awareness of Artificial Intelligence Tools. Sustainability, 17(15), 7092. https://doi.org/10.3390/su17157092.
Adel, A., Ahsan, A., & Davison, C. (2024). ChatGPT Promises and Challenges in Education: Computational and Ethical Perspectives. Education Sciences, 14(8), 814. https://doi.org/10.3390/educsci14080814.
Aggarwal, D. (2023). Adoption of Artificial Intelligence (AI) For Development of Smart Education as the Future of a Sustainable Education System. Journal of Artificial Intelligence Machine Learning and Neural Network, 3(6), 23-28. https://doi.org/10.55529/jaimlnn.36.23.28.
Antonopoulou, K., Begkos, C., & Zhu, Z. (2023). Staying afloat amidst extreme uncertainty: A case study of digital transformation in Higher Education. Technological Forecasting and Social Change, 192, 122603. https://doi.org/10.1016/j.techfore.2023.122603.
Baber, Z., Gibbons, M., Limoges, C., Nowotny, H., Schwartzman, S., Scott, P., & Trow, M. (1995). The New Production of Knowledge: The Dynamics of Science and Research in Contemporary Societies. Contemporary Sociology, 24(6), 751. https://doi.org/10.2307/2076669.
Baque Guerra, V. E., Zavala O’Brien, M. I., Mendoza Bajaña, V. P., Recalde Villacrés, E. B., Nevares Pacheco, M. D. J., Castillo Rodríguez, N. E., & Barreto Zúñiga, W. W. (2024). Percepciones y experiencias de docentes universitarios sobre la inteligencia artificial: Transformación, ética y desafíos en el uso académico por estudiantes. LATAM Revista Latinoamericana de Ciencias Sociales y Humanidades, 5(6). https://doi.org/10.56712/latam.v5i6.3204.
Bozkurt, A., Karadeniz, A., Baneres, D., Guerrero-Roldán, A. E., & Rodríguez, M. E. (2021). Artificial intelligence and reflections from educational landscape: A review of AI studies in half a century. Sustainability, 13(2), 1-16. https://doi.org/10.3390/su13020800.
Brajovic, D., Renner, N., Goebels, V. P., Wagner, P., Fresz, B., Biller, M., Klaeb, M., Kutz, J., Neuhuettler, J., & Huber, M. F. (2023). Model Reporting for Certifiable AI: A Proposal from Merging EU Regulation into AI Development (Versión 1). arXiv. https://doi.org/10.48550/ARXIV.2307.11525.
Chan, C. K. Y., & Zhou, W. (2023). An expectancy value theory (EVT) based instrument for measuring student perceptions of generative AI. Smart Learning Environments, 10(1). https://doi.org/10.1186/s40561-023-00284-4.
Chang, D. H., Lin, M. P.-C., Hajian, S., & Wang, Q. Q. (2023). Educational Design Principles of Using AI Chatbot That Supports Self-Regulated Learning in Education: Goal Setting, Feedback, and Personalization. Sustainability, 15(17). Scopus. https://doi.org/10.3390/su151712921.
Cheng, K., & Wu, H. (2024). Policy framework for the utilization of generative AI. Critical Care, 28(1), 128. https://doi.org/10.1186/s13054-024-04917-z.
Demchenko, M. V., Gulieva, M. E., Larina, T. V., & Simaeva, E. P. (2021). Digital Transformation of Legal Education: Problems, Risks and Prospects. European Journal of Contemporary Education, 10(2), 297-307. https://doi.org/10.13187/ejced.2021.2.297.
Floridi, L. (2023). The Ethics of Artificial Intelligence: Principles, Challenges, and Opportunities (1st ed.). Oxford University Press. https://doi.org/10.1093/oso/9780198883098.001.0001.
Holmes, W., Bialik, M., & Fadel, C. (2023). AI in education: Addressing challenges of equity and inclusion. Interactive Learning Environments, 31(2), 210-228. https://doi.org/10.1080/10494820.2023.2187798.
Hunton (April 21, 2025). Mexico overhauls federal data protection law. Hunton web page. https://www.hunton.com/privacy-and-information-security-law/mexico-overhauls-federal-data-protection-law.
Kitchenham, B., & Charters, S. (2007). Guidelines for performing Systematic Literature Reviews in Software Engineering. University of Durham.
Kohnke, L., Moorhouse, B. L., & Zou, D. (2023). Exploring generative artificial intelligence preparedness among university language instructors: A case study. Computers and Education: Artificial Intelligence, 5, 100156. https://doi.org/10.1016/j.caeai.2023.100156.
Mahrishi, M., Abbas, A., & Siddiqui, M. K. (2025). Global Initiatives Towards Regulatory Frameworks for Artificial Intelligence (AI) in Higher Education. Digital Government: Research and Practice, 6(2), 1-9. https://doi.org/10.1145/3672462.
Oncioiu, I., & Bularca, A. R. (2025). Artificial Intelligence Governance in Higher Education: The Role of Knowledge-Based Strategies in Fostering Legal Awareness and Ethical Artificial Intelligence Literacy. Societies, 15(6), 144. https://doi.org/10.3390/soc15060144.
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). Declaración PRISMA 2020: Una guía actualizada para la publicación de revisiones sistemáticas. Revista Española de Cardiología, 74(9), 9. https://doi.org/10.1016/j.recesp.2021.06.016.
Peláez-Sánchez, I. C., Velarde-Camaqui, D., & Glasserman-Morales, L. D. (2024). The impact of large language models on higher education: Exploring the connection between AI and Education 4.0. Frontiers in Education, 9, 1392091. https://doi.org/10.3389/feduc.2024.1392091.
Ruvalcaba‐Gomez, E. A., & Garcia‐Benitez, V. H. (2025). Governance of Artificial Intelligence in the Public Sector: Analysis of Public Policies in Spain and Mexico. Review of Policy Research, 70057. https://doi.org/10.1111/ropr.70057.
Tecnológico de Monterrey (2024a). Lineamientos para el uso ético de inteligencia artificial (profesorado). ITESM. https://tec.mx/sites/default/files/repositorio/integridad-academica/lineamientos-ia-profesores-tec-de-monterrey.pdf.
Tecnológico de Monterrey (2024b). Guía rápida para estudiantes: lineamientos de IA. ITESM. https://tec.mx/sites/default/files/repositorio/integridad-academica/guia-rapida-alumnos-inteligencia-artificial.pdf.
Universidad de Guadalajara (2024). Dictamen I/2024/018 (creación de plan relacionado con IA educativa). UdeG. https://cugdl.udg.mx/sites/default/files/adjuntos/dictamen-liac.pdf.
Universidad de Guadalajara (2024). Acuerdo No. RG/005/2024. UdeG. https://secgral.udg.mx/sites/default/files/Acuerdos/Acuerdo%20No.%20RG%2005%202024.pdf.
Universidad de Guadalajara (2023). Orientaciones y definiciones sobre el uso de la inteligencia artificial. UdeG Virtual. https://www.udgvirtual.udg.mx/sites/default/files/adjuntos/guia_ia_udg.pdf.
Universidad Nacional Autónoma de México (2024). Recomendaciones para el uso de la inteligencia artificial generativa en educación. UNAM. https://iagenedu.unam.mx/recomendaciones/.
Zawacki-Richter, O., Marín, V. I., & Bond, M. (2023). Evaluating institutional policies for AI adoption in education. Educational Media International, 60(1), 45-61. https://doi.org/10.1080/09523987.2023.2224352.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Iván Miguel García López, Jessica Nájera Ochoa
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
All contents of the electronic edition of the journal are distributed under a license and distribution "Creative Commons Attribution-Noncommercial-ShareAlike 4.0 International" (CC-BY-NC-SA). You can see from here the informative version of the license.
Those authors/publications as having this journal agree to the following terms:
a) Is allowed and recommends authors / as disseminate their work via the Internet (p. eg .: institutional telematic files or on their website), which can produce interesting exchanges and increase appointments of the published work. (See The Effect of Open Access).
