Integration of artificial intelligence applications in the management of higher Education Institutions: A critical review of the literature and emerging practices to enhance institutional efficiency and digital governance

Main Article Content

Tahani Abdullah Abdurhman Alhumud

Abstract

This article examines how artificial intelligence (AI) is being integrated into the management of higher education institutions (HEIs), with particular attention to institutional efficiency, digital governance, strategic decision-making, quality assurance, and student support. The paper addresses a persistent gap in the literature: while AI in higher education is commonly discussed in relation to teaching, learning, and assessment, far less work has synthesized AI as a management and governance phenomenon at the institutional level. The study therefore develops a PRISMA-informed critical review of research published primarily from 2018 to early 2026, drawing on scholarship from higher education studies, learning analytics, educational technology, public management, and digital governance. The review argues that AI in HEI management should not be understood merely as a set of efficiency tools. Rather, AI reconfigures administrative rationalities, redistributes managerial authority, transforms the visibility of institutional processes, and intensifies the role of data infrastructures in governance. Across the literature, the strongest evidence concerns student advising, retention analytics, administrative chatbots, and institutional monitoring systems; however, evidence is much thinner for finance, human resources, and long-term strategic planning. The article proposes a typology of AI-enabled management functions, distinguishes operational efficiency from governance transformation, and advances an integrative model linking AI adoption, institutional efficiency, and digital governance. It concludes that universities need human-centred AI governance, robust data stewardship, transparent accountability structures, and context-sensitive implementation strategies if AI is to support institutional improvement without deepening surveillance, opacity, or inequality.

Downloads

Download data is not yet available.

Article Details

How to Cite
Abdurhman Alhumud, T. A. (2026). Integration of artificial intelligence applications in the management of higher Education Institutions: A critical review of the literature and emerging practices to enhance institutional efficiency and digital governance. Research Journal in Advanced Humanities, 7(1). https://doi.org/10.58256/fcrd3d96
Section
Articles

How to Cite

Abdurhman Alhumud, T. A. (2026). Integration of artificial intelligence applications in the management of higher Education Institutions: A critical review of the literature and emerging practices to enhance institutional efficiency and digital governance. Research Journal in Advanced Humanities, 7(1). https://doi.org/10.58256/fcrd3d96

Share

References

Adams, C., Pente, P., Lemermeyer, G., & Rockwell, G. (2023). Ethical principles for artificial intelligence in education. Computers and Education: Artificial Intelligence, 4, 100131.

Akgun, S., & Greenhow, C. (2022). Artificial intelligence in education: Addressing ethical challenges in K-12 settings. AI and Ethics, 2(3), 431-440. https://doi.org/10.1007/s43681-021-00096-7

Baker, R. S., & Hawn, A. (2022). Algorithmic bias in education. International Journal of Artificial Intelligence in Education, 32, 1052-1092. https://doi.org/10.1007/s40593-021-00285-9

Beer, D. (2017). The social power of algorithms. Information, Communication & Society, 20(1), 1-13. https://doi.org/10.1080/1369118X.2016.1216147

Benayoune, A., et al. (2026). Artificial intelligence policy challenges and institutional priorities in higher education. Discover Education, 5, Article 188.

Bond, M., Khosravi, H., de Laat, M., Bergdahl, N., Negrea, V., Oxley, E., Pham, P., Wang Chong, S., & Siemens, G. (2024). A meta systematic review of artificial intelligence in higher education: A call for increased ethics, collaboration, and rigour. International Journal of Educational Technology in Higher Education, 21, Article 4. https://doi.org/10.1186/s41239-023-00436-z

Budhathoki, T., Grover, V., Gyamfi, E., & Jafri, S. M. A. H. (2024). ChatGPT adoption and anxiety: A cross-country analysis of higher education students in Nepal and the UK. Studies in Higher Education. Advance online publication. https://doi.org/10.1080/03075079.2024.2333937

Chiu, T. K. F., Xia, Q., Zhou, X., Chai, C. S., & Cheng, M. (2023). Systematic literature review on opportunities, challenges, and future research recommendations of artificial intelligence in education. Computers and Education: Artificial Intelligence, 4, 100118. https://doi.org/10.1016/j.caeai.2022.100118

Cormack, A. N. (2016). A data protection framework for learning analytics. Journal of Learning Analytics, 3(1), 91-106.

De Silva, L. M. H., et al. (2025). A needs analysis for institutional analytics. Studies in Higher Education. Advance online publication. https://doi.org/10.1080/03075079.2025.2596129

Diaz Lema, M., et al. (2024). Predicting dropout in higher education across borders. Studies in Higher Education, 49, 1-16. https://doi.org/10.1080/03075079.2023.2224818

Dumitru, C., et al. (2025). Integrating artificial intelligence in supporting students with disabilities in higher education: An integrative review. Review of Education.

European Commission. (2022). Ethical guidelines for educators on the use of artificial intelligence and data in teaching and learning. Brussels: European Commission.

European Commission. (2024). AI Act enters into force. Brussels: European Commission.

Gašević, D., Dawson, S., & Siemens, G. (2015). Let’s not forget: Learning analytics are about learning. TechTrends, 59(1), 64-71. https://doi.org/10.1007/s11528-014-0822-x

Gašević, D., Tsai, Y.-S., Jovanović, J., & Pardo, A. (2022). Learning analytics in higher education: Stakeholders, strategy development, and scalable adoption. The Internet and Higher Education, 53, 100846.

Gillespie, T. (2014). The relevance of algorithms. In T. Gillespie, P. Boczkowski, & K. Foot (Eds.), Media technologies: Essays on communication, materiality, and society (pp. 167-194). MIT Press. https://doi.org/10.7551/mitpress/9780262525374.003.0009

Ifenthaler, D., & Yau, J. Y.-K. (2020). Utilising learning analytics to support study success in higher education: A systematic review. Educational Technology Research and Development, 68, 1961-1990. https://doi.org/10.1007/s11423-020-09788-z

Isaifan, R. J., et al. (2025). Artificial intelligence for quality assurance in higher education. Quality in Higher Education. Advance online publication. https://doi.org/10.1080/13538322.2025.2576326

Johnson, D. L., et al. (2024). Personalized AI solutions for college access and learning. New Directions for Higher Education, 207, 83-92.

Jones, K. M. L. (2019). Learning analytics and higher education: A proposed model for establishing informed consent mechanisms to promote student privacy and autonomy. International Journal of Educational Technology in Higher Education, 16, Article 24. https://doi.org/10.1186/s41239-019-0155-0

Jwair, A. A. B. (2025). Generative artificial intelligence in higher education. Cogent Education, 12, Article 2589495.

Kitchin, R. (2017). Thinking critically about and researching algorithms. Information, Communication & Society, 20(1), 14-29. https://doi.org/10.1080/1369118X.2016.1154087

Kosbar, Y. (2025). Towards human-centred, ethical and inclusive use and governance of AI in higher education. Journal of Transformative Education.

Kuhail, M. A., et al. (2023). Engaging students with a chatbot-based academic advising system. International Journal of Human-Computer Interaction, 39, 1-19. https://doi.org/10.1080/10447318.2022.2074645

Liang, J., et al. (2025). A systematic review of the early impact of artificial intelligence in higher education. Frontiers in Education, 10, 1522841.

Lim, T., et al. (2025). What students really think: Unpacking AI ethics in educational settings. International Journal of Educational Technology in Higher Education, 22, Article 56.

Machkour, B., et al. (2025). The rise of artificial intelligence in educational management. Procedia Computer Science, 245, 902-909.

Mandinach, E. B. (2025). Artificial intelligence in data-driven decision making. Cogent Education, 12, Article 2584802.

Marín, Y. R., et al. (2025). Ethical challenges associated with the use of artificial intelligence in universities. Journal of Academic Ethics. Advance online publication. https://doi.org/10.1007/s10805-025-09660-w

Marland, B., & Arantes, J. (2026). Reframing AI governance in education: Insights from the social model of disability. Learning, Media and Technology. Advance online publication. https://doi.org/10.1080/17439884.2025.2595443

Marzouk, O. A., et al. (2025). Benchmarking retention, progression, and graduation rates in higher education. Cogent Education, 12, Article 2498170.

Mathew, B. J., et al. (2023). How does academic advising influence student learning outcomes? Cogent Education, 10, Article 2197663.

Matos, T., et al. (2025). A systematic review of artificial intelligence applications in education. Computers and Education Open, 6, 100184.

McCarthy, S., et al. (2025). Personalising with AI in higher education. Higher Education Research & Development. Advance online publication.

Meeter, M., et al. (2023). Predicting retention in higher education from high-stakes exams and prior attainment. College and University, 98(1), 1-18.

Mohiuddin, K., et al. (2023). Potentialities and priorities for higher educational development in Saudi Arabia for the achievement of Vision 2030. Heliyon, 9, e21924.

Murni, S. (2026). Artificial intelligence in higher education management: A bibliometric analysis of challenges, opportunities, and future research directions. Discover Education, 5, Article 165.

Mutimukwe, C., et al. (2022). Students’ privacy concerns in learning analytics: Model development and validation. British Journal of Educational Technology, 53, 782-799.

Nartey, E. K. (2024). Guiding principles of generative AI for employability and educational policy. Cogent Education, 11, Article 2357898.

Nguyen, A., Ngo, H., Hong, Y., Dang, B., & Nguyen, B. P. T. (2023). Ethical principles for artificial intelligence in education. Education and Information Technologies, 28(4), 4221-4241. https://doi.org/10.1007/s10639-022-11316-w

Nirala, K. K., Singh, A., & Ahuja, N. J. (2022). A survey on providing customer and public administration services based on AI-chatbots. Multimedia Tools and Applications, 81, 22255-22293.

Noroozi, O., & colleagues. (2025). Artificial intelligence in higher education: Impact depends on context. Innovations in Education and Teaching International.

Noroozi, O., et al. (2025). Artificial intelligence in higher education: Impact depends on context. Innovations in Education and Teaching International. Advance online publication. https://doi.org/10.1080/14703297.2025.2539579

Ocen, S., et al. (2025). Artificial intelligence in higher education institutions: Review of innovations, opportunities and challenges. Frontiers in Education, 10, 1530247.

OECD. (2024). The potential impact of artificial intelligence on equity and inclusion in education. Paris: OECD.

Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., et al. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71

Parakhina, V. N., et al. (2017). Strategic management in universities as a factor of their global competitiveness. International Journal of Educational Management, 31(1), 62-75.

Pargman, T. C., & McGrath, C. (2021). Mapping the ethics of learning analytics in higher education: A systematic literature review of empirical research. Journal of Learning Analytics, 8(2), 123-139.

Parker, L., et al. (2025). Comparative analysis of artificial intelligence policies in higher education institutions. Innovative Higher Education. Advance online publication. https://doi.org/10.1007/s10791-025-09745-5

Peyton, K., Unnikrishnan, S., & Mulligan, B. (2025). A review of university chatbots for student support: FAQs and beyond. Discover Education, 4, Article 21. https://doi.org/10.1007/s44217-025-00397-7

Prinsloo, P., & Slade, S. (2016). Student vulnerability, agency and learning analytics: An exploration. Journal of Learning Analytics, 3(1), 159-182.

Prinsloo, P., & Slade, S. (2017). An elephant in the learning analytics room: The obligation to act. Proceedings of the Seventh International Learning Analytics & Knowledge Conference, 46-55.

Richter, S., et al. (2025). Chatbots in tertiary education: Exploring the impact of warm and competent chatbot avatars. British Journal of Educational Technology. Advance online publication. https://doi.org/10.1111/bjet.13610

Roca, M. D. L., et al. (2024). The impact of a chatbot working as an assistant in a course. Computer Applications in Engineering Education, 32(4), e22750.

Ross, O., et al. (2025). Lessons learnt from a substantial gain in student retention. Irish Educational Studies. Advance online publication. https://doi.org/10.1080/03323315.2025.2584016

Sabzalieva, E., & Valentini, A. (2023). ChatGPT and artificial intelligence in higher education: Quick start guide. UNESCO IESALC.

Schmidt, D. A., et al. (2025). Integrating artificial intelligence in higher education. Smart Learning Environments, 12, Article 33.

Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. Polity.

Shum, S. B., & Ferguson, R. (2012). Social learning analytics. Educational Technology & Society, 15(3), 3-26.

Siddiq, F., et al. (2025). Towards a code of ethics for using technology-enabled analytics in education. Assessment & Evaluation in Higher Education. Advance online publication. https://doi.org/10.1080/0969594X.2025.2453138

Siemens, G. (2013). Learning analytics: The emergence of a discipline. American Behavioral Scientist, 57(10), 1380-1400.

Siu, B., et al. (2025). What influences student intentions to use generative AI in higher education? British Educational Research Journal. Advance online publication. https://doi.org/10.1002/berj.4206

Slade, S., & Prinsloo, P. (2013). Learning analytics: Ethical issues and dilemmas. American Behavioral Scientist, 57(10), 1510-1529.

Smith, S. M., Tate, M., Freeman, K., Walsh, A., Ballsun-Stanton, B., Hooper, M., & Lane, M. (2026). A university framework for the responsible use of generative AI in research. Journal of Higher Education Policy and Management, 48(1), 17-36. https://doi.org/10.1080/1360080X.2025.2509187

Sohrabi, C., et al. (2021). PRISMA 2020 statement: What’s new and the importance of reporting guidelines. International Journal of Surgery, 88, 105918.

Sorour, A., et al. (2024). Big data challenge for monitoring quality in higher education. Tsinghua Journal of Education, 45(1), 1-18.

Thaldar, D., Botes, M., Badru, A., Chenia, H., Duma, S., Dlamini, S. B., Amin, N., Hugo, W., Govender, R., Bruce-Brand, J., Vosloo, A., Koorbanally, N. A., & Chuturgoon, A. (2025). Generative AI governance in higher education: A case study from Africa. Frontiers in Political Science, 7, 1666661. https://doi.org/10.3389/fpos.2025.1666661

Tsai, Y.-S., Moreno-Marcos, P. M., Jivet, I., Scheffel, M., Tammets, K., Kollom, K., & Gašević, D. (2021). The SHEILA framework: Informing institutional strategies and policies for learning analytics. Journal of Learning Analytics, 8(3), 9-34.

Umer, R., Susnjak, T., Mathrani, A., & Suriadi, S. (2023). Current stance on predictive analytics in higher education: Review and open challenges. Interactive Learning Environments, 31(10), 6988-7004. https://doi.org/10.1080/10494820.2021.1933542

UNESCO. (2021). AI and education: Guidance for policy-makers. Paris: UNESCO.

UNESCO. (2023). Guidance for generative AI in education and research. Paris: UNESCO.

Wang, S. (2024). Algorithmic decisions in education governance. Discover Education, 3, Article 337.

Wang, S., Wang, F., Zhu, Z., Wang, J., Tran, T., & Du, Z. (2024). Artificial intelligence in education: A systematic literature review. Expert Systems with Applications, 252, 124167. https://doi.org/10.1016/j.eswa.2024.124167

Webber, K. L., & Zheng, H. Y. (2024). Artificial intelligence and advanced data analytics: Implications for higher education. New Directions for Higher Education, 207, 5-13. https://doi.org/10.1002/he.20508

Wickramasinghe, M., et al. (2026). Ethical principles for artificial intelligence in education: A meta-review approach. AI and Ethics, 6, Article 63.

Williamson, B. (2017). Big data in education: The digital future of learning, policy and practice. SAGE.

Williamson, B., Bayne, S., & Shay, S. (2020). The datafication of teaching in higher education: Critical issues and perspectives. Teaching in Higher Education, 25(4), 351-365. https://doi.org/10.1080/13562517.2020.1748811

Williamson, B., Eynon, R., & Potter, J. (2020). Pandemic politics, pedagogies and practices: Digital technologies and distance education during the coronavirus emergency. Learning, Media and Technology, 45(2), 107-114.

Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education - where are the educators? International Journal of Educational Technology in Higher Education, 16, Article 39. https://doi.org/10.1186/s41239-019-0171-0