Evolution of Artificial Intelligence (AI)-driven Information Systems in Higher Education: A Review
Keywords:
Adaptive Learning, Artificial Intelligence, Data Ethics, Educational Technology, Higher Education, Information SystemAbstract
Artificial Intelligence (AI) has fundamentally reshaped the
architecture of Information Systems (IS) within higher
education institutions. This systematic literature review
examines the technological transition from traditional
management databases to intelligent, autonomous
frameworks. By analyzing peer-reviewed studies published
over the last decade, this paper identifies three major
evolutionary phases: the automation of administrative tasks,
the rise of adaptive learning platforms, and the integration
of predictive analytics for student success. The findings
highlight how AI-driven systems enhance operational
efficiency and personalize student experiences while
simultaneously introducing complex challenges regarding
data ethics and algorithmic bias. This review provides a
comprehensive synthesis of current trends, offering a
strategic roadmap for educators and technologists to
navigate the future of intelligent academic ecosystems.
References
Sinaga, D. A. M. B., and Nandiyanto, A. B. D. (2022). Clean living culture through online
learning using digital media for junior high school students. International Journal of
Research and Applied Technology (INJURATECH), 2(1), 100-107.
Ashraf, S. R. (2024). The role of artificial intelligence in enhancing managerial decision-making
in education. International Journal of Advanced Social Sciences Research, 1(1), 10-20.
Zimosz, P., and Ober, J. (2025). Impact of Artificial Intelligence on Education. Knowledge
Economy and Lifelong Learning, 1(2), 77-98.
Pangaribuan, I., Rahman, A., and Mauluddin, S. (2020). Computer & network equipment
management system (CNEMAS) application measurement. International Journal of
Informatics, Information System and Computer Engineering (INJIISCOM), 1(1), 23-34.
Gonugunta, K. C., and Leo, K. (2024). Role of data-driven decision making in enhancing higher
education performance: A comprehensive analysis of analytics in institutional
management. International Journal of Acta Informatica, 3(1), 149-159.
Chen, J. M., Zhang, L., Pengnate, S., Ma, E., and Leung, X. Y. (2025). Integrating a custom
chatbot into higher education: From passive to interactive e-learning. Journal of
Information Systems Education, 36(4), 384-399.
Aras, S., Kelian, M. N., and Faridah, A. (2025). AI-based chatbot system for education and
recommendations on the use of native Papuan herbal plants using the Large Language
Models method. International Journal of Informatics, Information System and Computer
Engineering (INJIISCOM), 6(1), 96-105.
Salman, Z. M., and Nandiyanto, A. B. D. (2022). Literature about maintaining physical fitness
through digital in community. International Journal of Research and Applied Technology
(INJURATECH), 2(1), 124-131.
Soegoto, E. S., Ananta, H., Zaki, I., and Ranau, M. I. N. (2022). Implementation of management
information system using machine learning technology. International Journal of Research
and Applied Technology (INJURATECH), 2(2), 220-228.
Schneider, J. (2024). Explainable generative AI (GenXAI): A survey, conceptualization, and
research agenda. Artificial Intelligence Review, 57(11), 289.
Bernal, M. E. (2024). Revolutionizing eLearning assessments: The role of GPT in crafting
dynamic content and feedback. Journal of Artificial Intelligence and Technology, 4(3),
-199.
Zangana, H. M., and Zeebaree, S. R. (2024). Distributed systems for artificial intelligence in
cloud computing: A review of AI-powered applications and services. International Journal
of Informatics, Information System and Computer Engineering (INJIISCOM), 5(1), 11-30.
Jayaram, Y., Sundar, D., and Bhat, J. (2022). AI-driven content intelligence in higher education:
Transforming institutional knowledge management. International Journal of Artificial
Intelligence, Data Science, and Machine Learning, 3(2), 132-142.
Kothandapani, H. P. (2025). AI-driven regulatory compliance: Transforming financial oversight
through large language models and automation. Emerging Science Research, 12(1), 12
Müller, O., Junglas, I., Brocke, J. V., and Debortoli, S. (2016). Utilizing big data analytics for
information systems research: Challenges, promises and guidelines. European Journal of
Information Systems, 25(4), 289-302.
Albaroudi, E., Mansouri, T., and Alameer, A. (2024). A comprehensive review of AI techniques
for addressing algorithmic bias in job hiring. Ai, 5(1), 383-404.
Jabbar, F. A., and Rithanya, K. S. (2021). Risks of chronic kidney disease prediction using
various data mining algorithms. International Journal of Informatics, Information System
and Computer Engineering (INJIISCOM), 2(2), 165-177.
Aniru, M. A., Osasenaga, E. V., Emmanuel, O. E., Gerald, M. O., and Melody, E. O. (2025).
Design and construction of a smart lock system using Internet of Things
(IoT). International Journal of Informatics, Information System and Computer Engineering
(INJIISCOM), 6(1), 82-95.
Chatti, H., and Argoubi, M. (2025). Artificial Intelligence in Knowledge Management:
Identifying Intellectual Milestones and Emerging Domains. Electronic Journal of
Knowledge Management, 23(2), 122-148.
Rahate, V., Mehta, A. K., Deshpande, S., Jawarkar, P., Disawal, V., and Sarge, P. (2025). Impact
of AI-Driven Learning Management Systems on Institutional Efficiency and Student
Engagement. Metallurgical and Materials Engineering, 31(2), 98-103.
Champaneria, H. K. (2025). From Insight to Impact: Architecting AI-Driven Learning
Ecosystems for Personalized, Predictive, and Proactive Education. Journal Of Applied
Sciences, 5(12), 10-20.
Jain, H., Padmanabhan, B., Pavlou, P. A., and Raghu, T. S. (2021). Editorial for the special
section on humans, algorithms, and augmented intelligence: The future of work,
organizations, and society. Information Systems Research, 32(3), 675-687.
