The Implementation of Artificial Intelligence (AI) in Effective and Accurate Strategic Decision-Making in Higher Education Environments
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Abstract
The increasingly complex higher education environment demands a more effective and accurate data-driven strategic decision-making approach. This study aims to analyze the implementation of Artificial Intelligence (AI) in supporting the effectiveness and accuracy of strategic decision-making in the higher education environment. This article uses a literature review approach with descriptive analysis methods. This approach was conducted by collecting, analyzing, and synthesizing various scientific literature related to the application of Artificial Intelligence (AI) in supporting the effectiveness and accuracy of strategic decision-making in higher education environments. The results show that the implementation of AI, although still in its early stages, has significantly improved predictive accuracy and objectivity in various strategic areas, such as 1) student recruitment; 2) student retention; 5), and resource allocation. Qualitative findings reveal that AI acts as a powerful decision support system. However, the main challenges are non-technical in nature, namely: 1) data quality and availability, 2) lack of expert human resources, and 3) organizational cultural resistance. Based on these findings, the researchers recommend that in order to maximize the benefits of Artificial Intelligence (AI) in strategic decision-making effectively and accurately, universities need to invest in data infrastructure, human resource capacity, and ethical policies, while ensuring that human leadership remains the final decision-maker that considers the values and context of the institution.
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References
Alsalman, A. I. (2024). Artificial Intelligence and its influence on strategic decision-making: An exploration at Imam Abdulrahman Bin Faisal University, Saudi Arabia. Journal of International Crisis and Risk Communication Research, 7(S7), 560-578. https://doi.org/10.63278/jicrcr.vi.1383.
Ary, M., Andriani, R., & Fauzzia, W. (2025). Optimizing decision-making in higher education institutions through AI-driven business intelligence in the digital era. International Journal of Economics, Management and Accounting (IJEMA), 3(3), 221-229. https://doi.org/10.47353/ijema.v3i3.328.
Aydin, B., & Yurdakul, I. K. (2023). Exploring the impact of AI-based early warning systems on student retention in higher education. Education and Information Technologies, 28(4), 5127–5144. https://doi.org/10.1007/s10639-023-11842-1.
Baker, R. S. (2016). Stupid Tutoring Systems, Intelligent Humans. International Journal of Artificial Intelligence in Education, 26(2), 600-614.
Baker, R. S., Inventado, P. S., Tissenbaum, M., & Ogan, A. (2024). New advances in artificial intelligence applications in higher education? International Journal of Educational Technology in Higher Education, 21(32). https://doi.org/10.1186/s41239-024-00464-3
Ben Kasmia, N., Hamiche, M., & Chatit, F. (2025). Enhancing strategic decision-making in higher education institutions in Morocco: Formulating composite indexes for SVM machine learning models. Isagoge - Journal of Humanities and Social Sciences, 5(1). https://doi.org/10.59079/isagoge.v5i1.272.
Braun, V., & Clarke, V. (2022). Thematic analysis: A practical guide. Sage Publications.
Brown, M., & Lippincott, S. (2017). Digital Transformation in Higher Education: The Future of Learning, Teaching, and Research. EDUCAUSE Review.
Chan, C. Y. (2023). A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, 20, Article 38. https://doi.org/10.1186/s41239-023-00408-3.
Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: the state of the field. International Journal of Educational Technology in Higher Education, 20, Article 22. https://doi.org/10.1186/s41239-023-00392-8
Fadlelmula, F. K., & Qadhi, S. M. (2024). A systematic review of research on artificial intelligence in higher education: Practice, gaps, and future directions in the GCC. Journal of University Teaching and Learning Practice, 21(06). https://doi.org/10.53761/pswgbw82
Farber, S. (2025). Enhancing academic decision-making: A pilot study of AI-supported journal selection in higher education. Innovative Higher Education, 50, 1813-1831. https://doi.org/10.1007/s10755-025-09791-3.
Gadmi, M. A., Loulid, A., & Bendarkawi, Z. (2024). The integration of artificial intelligence into education systems and its impact on higher education governance. Education and Information Technologies, 29(5), 9123–9145. https://doi.org/10.1007/s10639-024-12612-5
Garg, A., Mohanty, S., Bh, R., S, L., Burbure, P., & Ashokkumar, N. (2025). Artificial intelligence and strategic management: A framework for smart educational institutions. Lex Localis - Journal of Local Self-Government, 23(S3), 219-228. https://doi.org/10.52152/.
Houghton, R., Zhai, X., Li, Z., & Large, D. (2025). Human-AI decision-making in higher education: A socio-technical perspective. Proceedings of Ergonomics & Human Factors 2025, 142–155.
Ifeanyi, A. J., Dudutari, B., & Orie Apkubi, R. (2024). Artificial Intelligence and strategic decision-making: Investigating how AI tools shape strategic planning and resource allocation. BW Academic Journal, ISSN: 4X60 – 6539, Volume 10, Number 3, 2025.
Li, Y. (2022). Machine learning for enrollment prediction and strategic planning in universities. Applied Artificial Intelligence, 36(1), 88–104. https://doi.org/10.1080/08839514.2021.2000211.
Marinoni, G., Van’t Land, H., & Jensen, T. (2020). The Impact of COVID-19 on Higher Education Around the World. International Association of Universities (IAU) Global Survey Report.
McConvey, K., Guha, S., & Kuzminykh, A. (2023). A human-centered review of algorithms in decision-making in higher education. Computers & Education: Artificial Intelligence, 5, 100137. https://doi.org/10.1016/j.caeai.2023.100137
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71.
Popenici, S. A. D., & Kerr, S. (2017). Exploring the Impact of Artificial Intelligence on Teaching and Learning in Higher Education. Research and Practice in Technology Enhanced Learning, 12(1), 22.
Sclater, N., Peasgood, A., & Mullan, J. (2016). Learning Analytics in Higher Education: A review of UK and international practice. Jisc.
Smith, J., & Jones, M. (2022). Bridging the AI talent gap in academia: Barriers and strategies for higher education institutions. AI and Society, 37(4), 1731–1746. https://doi.org/10.1007/s00146-022-01468.
Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–339. https://doi.org/10.1016/j.jbusres.2019.07.039.
Xiao, Y., & Watson, M. (2019). Guidance on conducting a systematic literature review. Journal of Planning Education and Research, 39(1), 93–112. https://doi.org/10.1177/0739456X17723971.