AI-Enabled Academic Administration and Process Optimization in Higher Education Institutions

Authors

Zhang Yajie

Philippine Christian University, Malate, Manila 1004, (Philippines); Inner Mongolia Electronic Information Vocational Technical College Saihan District, Hohhot, Inner Mongolia (China)

Article Information

DOI: 10.47772/IJRISS.2026.100300498

Subject Category: Artificial Intelligence

Volume/Issue: 10/3 | Page No: 6855-6865

Publication Timeline

Submitted: 2026-03-25

Accepted: 2026-03-30

Published: 2026-04-14

Abstract

This conceptual paper explored the potential of artificial intelligence (AI) to optimize administrative processes in higher education. Its purpose is threefold: to review current literature on AI applications in university administration, to propose a conceptual framework for process optimization, and to outline the institutional and ethical conditions necessary for responsible adoption. Drawing on an integrative literature review and conceptual analysis, the study synthesizes insights from educational technology, organizational theory, and digital ethics to construct a four-part framework comprising transactional automation, predictive intelligence, conversational service, and strategic governance. Each dimension addresses specific sources of administrative friction—workflow inefficiency, delayed decision-making, information inaccessibility, and institutional misalignment—while collectively supporting coherent, data-informed, and human-centered operations. The framework emphasizes that AI is not a stand-alone solution; meaningful gains require alignment with process redesign, data interoperability, iterative implementation, and robust human oversight. Ethical and organizational risks—including algorithmic bias, privacy and surveillance concerns, deskilling, and strategic distraction—are highlighted, reinforcing the necessity of transparency, accountability, and governance structures in implementation. By positioning AI as a layered capability rather than a set of isolated tools, the framework provides higher education institutions with guidance for deploying AI responsibly, ensuring that efficiency improvements are accompanied by fairness, student-centeredness, and institutional legitimacy. The study contributes both a theoretical lens and practical implications for administrators, policymakers, and institutional planners aiming to integrate AI into academic administration thoughtfully and strategically.

Keywords

AI in higher education, academic administration, process optimization

Downloads

References

1. Bantugan, B. (2023). Integral human development in higher education and HIV-AIDS advocacy work of Filipino artists. East Asian Journal of Multidisciplinary Research, 2(2), 473–496. https://doi.org/10.55927/eajmr.v2i2.2966 [Google Scholar] [Crossref]

2. Bantugan, B. (2026). A multisectoral and democratized AI governance policy for St. Paul University Manila: Countering global techno-authoritarianism and abuse. International Journal of Research and Scientific Innovation, 13(1), 1040–1078. https://doi.org/10.51244/IJRSI.2026.13010093 [Google Scholar] [Crossref]

3. Bantugan, B. S., Bantugan, F. C., & Urbano, R. C. (2018). Bridging the age-related communication gap: An encounter between senior citizens and communication students towards social integration. Asian Journal for Public Opinion Research, 5(2), 84–103. https://doi.org/10.15206/ajpor.2018.5.2.84 [Google Scholar] [Crossref]

4. Bantugan, B., Bernardo, J., & Laqueo, G. (2025). Surfacing the qualitative mindset in Philippine graduate education: An interpretivist and constructivist analysis of CHED Memorandum Order No. 15, Series of 2019. International Journal of Research and Innovation in Social Science, 9(9), 8078–8096. [Google Scholar] [Crossref]

5. Bantugan, B., Montenegro, G., & Modesto, B. (2025). The National Arts Month of the Philippines, college students of St. Paul University Manila, and celebrating art in community. International Journal of Research and Scientific Innovation, 12(2), 1104–1118. https://doi.org/10.51244/IJRSI.2025.12021104 [Google Scholar] [Crossref]

6. Bantugan, B. S., & Valeriano, E. M. (2019). The culture of volunteerism among St. Paul University Manila student leaders. Paulinian Compass: The Asia-Pacific Journal on Compassion Studies, 5(3), 33–45. [Google Scholar] [Crossref]

7. Bantugan, B., Vaswani, J., Ogelasco, J., Villanueva, B., & Butial, A. (2025). Building the research knowledge management framework of the South Luzon cluster of the St. Paul of Chartres education ministry. International Journal of Arts and Social Science, 6(2). [Google Scholar] [Crossref]

8. Bond, M., Khosravi, H., De Laat, M., Bergdahl, N., & Gašević, D. (2024). Artificial intelligence in higher education: A systematic review of emerging practices and implications. Computers & Education, 194, 104708. https://doi.org/10.1016/j.compedu.2023.104708 [Google Scholar] [Crossref]

9. Chan, C. K. Y. (2023). A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, 20(1), 38. https://doi.org/10.1186/s41239-023-00392-4 [Google Scholar] [Crossref]

10. Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: The state of the field. Educational Technology Research and Development, 71(1), 1–28. https://doi.org/10.1007/s11423-022-10156-6 [Google Scholar] [Crossref]

11. Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108–116. [Google Scholar] [Crossref]

12. Hina, S., Dominic, P. D. D., & Ahmad, M. (2019). Information security policies' compliance: A perspective of higher education institutions. Journal of Information Security and Applications, 45, 122–132. [Google Scholar] [Crossref]

13. Khairullah, M., et al. (2025). Strategic leadership in the age of AI: Balancing efficiency and empathy in higher education. Journal of Educational Management. [Google Scholar] [Crossref]

14. Pacheco-Mendoza, J., López, G., & Ramírez, M. (2023). Predictive analytics in higher education: Early warning systems and student success. Education and Information Technologies, 28(6), 7451–7470. https://doi.org/10.1007/s10639-022-11456-7 [Google Scholar] [Crossref]

15. Prenkaj, B., Velardi, P., Stilo, G., Distante, D., & Faralli, S. (2020). A survey of machine learning approaches for student dropout prediction in online courses. ACM Computing Surveys, 53(3), 1–34. https://doi.org/10.1145/3388792 [Google Scholar] [Crossref]

16. Slade, S., & Prinsloo, P. (2013). Learning analytics: Ethical issues and dilemmas. American Behavioral Scientist, 57(10), 1510–1529. https://doi.org/10.1177/0002764213479366 [Google Scholar] [Crossref]

17. Torraco, R. J. (2005). Writing integrative literature reviews: Guidelines and examples. Human Resource Development Review, 4(3), 356–367. [Google Scholar] [Crossref]

18. Torraco, R. J. (2016). Writing integrative literature reviews: Using the past and present to explore the future. Human Resource Development Review, 15(4), 404–428. [Google Scholar] [Crossref]

19. UNESCO. (2021). Recommendation on the Ethics of Artificial Intelligence. United Nations Educational, Scientific and Cultural Organization. [Google Scholar] [Crossref]

20. UNESCO. (2023). Guidance for generative AI in education and research. United Nations Educational, Scientific and Cultural Organization. https://unesdoc.unesco.org/ark:/48223/pf0000386693 [Google Scholar] [Crossref]

21. Wang, Y., Liu, X., Zhang, Z., & Li, Q. (2024). Applications of artificial intelligence in higher education: A review of administrative and academic use cases. Education and Information Technologies, 29(2), 1453–1475. https://doi.org/10.1007/s10639-023-11988-7 [Google Scholar] [Crossref]

22. 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(1), 39. https://doi.org/10.1186/s41239-019-0171-0 [Google Scholar] [Crossref]

Metrics

Views & Downloads

Similar Articles