Cultivating Responsible Artificial Intelligence Practices in Malaysian Higher Education DOI: https://doi.org/10.33093/ijomfa.2026.7.1.16

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Published: Feb 28, 2026
DOI: https://doi.org/10.33093/ijomfa.2026.7.1.16
Keywords:
Artificial Intelligence Literacy, Artificial Intelligence Transparency, Data Privacy, Ethical Artificial Intelligence, Higher Education

Main Article Content

Sharfika Raime
City Graduate School, City University Malaysia, Selangor, Malaysia.
https://orcid.org/0000-0003-2649-0610
Norsafriman Abd. Rahman
UNITAR College, Selangor, Malaysia.
Raemah Abdullah Hashim
City Graduate School, City University Malaysia, Selangor, Malaysia.
Mohd. Farid Shamsudin
UniKL Business School, Universiti Kuala Lumpur, Kuala Lumpur, Malaysia.

Abstract

The integration of Artificial Intelligence (AI) in higher education presents both opportunities and ethical challenges. In Malaysia, private universities are adopting AI at a pace that often outshines the development of governance frameworks, raising concerns over transparency, data privacy, and ethical literacy. This research examines the influence of three predictors (AI Transparency, Data Privacy Awareness, and Ethical AI Literacy) on the ethical use of AI among 221 academicians. Guided by Deontological Ethical Theory and employing a quantitative correlational design, the analysis revealed strong and significant relationships among all variables. Data Privacy Awareness emerged as the most consistent and positive predictor of ethical AI usage. Interestingly, AI Transparency and Ethical AI Literacy showed suppressor effects, meaning their predictive power became clearer when accounting for the influence of other variables. The model achieved an R² value of 0.653, indicating that the predictors explained 65.3% of the variance in ethical AI behaviours. The research makes three key contributions. Firstly, it addresses a gap in AI ethics research within Malaysian private universities, integrating philosophical and empirical perspectives to inform governance. Lastly, it provides actionable insights for policy and training. By emphasising the need for transparent practices, robust data protection, and ethical literacy programmes, the findings directly support SDG 4 (Quality Education) by promoting responsible digital competencies and SDG 16 (Peace, Justice and Strong Institutions) by encouraging ethical governance in AI adoption.

Article Details

How to Cite
Raime, S., Abd. Rahman, N. ., Abdullah Hashim, R., & Shamsudin, M. F. (2026). Cultivating Responsible Artificial Intelligence Practices in Malaysian Higher Education: DOI: https://doi.org/10.33093/ijomfa.2026.7.1.16. International Journal of Management, Finance and Accounting, 7(1), 448–474. https://doi.org/10.33093/ijomfa.2026.7.1.16
Issue
Vol. 7 No. 1 (2026)
Section
Management, Finance and Accounting
Author Biographies

Sharfika Raime, City Graduate School, City University Malaysia, Selangor, Malaysia.

Sharfika Raime is a Senior Lecturer at CITY University Malaysia. She received degrees in Business Administration (Curtin University), Master in Project Management (Open University Malaysia), and a PhD in Management (University Kuala Lumpur). With years of experience in academia and the oil and gas industry, she brings a unique blend of expertise to her role. Her research focuses on human resource management, education, tourism, and technology management. Since 2023, she has been actively involved in research consultancy and collaborative projects across sectors. She also plays a key role in securing matching grants for research and publication with renowned universities locally and internationally. She can be contacted at email: sharfika.raime@city.edu.my

Norsafriman Abd. Rahman, UNITAR College, Selangor, Malaysia.

Norsafriman B. Abd Rahman holds an MBA (IMI Switzerland, 2008), a B.Sc. in Marketing (RIT USA, 1998), and a Diploma in Banking Studies (UiTM, 1994). He has taught diploma and bachelor-level courses at UNITAR since 1999. His earlier career included roles in hospitality, manufacturing, and retail. His research spans social sciences, encompassing cultural tourism (2006–2011); business management, education management and technology management (2018 onward). Since the early 2000s, he has also provided consultancy in events and F&B. He can be contacted at email: safriman@unitar.my

References

Alzoubi, Y. I., & Mishra, A. (2025). Differential privacy and artificial intelligence: potentials, challenges, and future avenues. Eurasip Journal on Information Security, 2025:18, 1–19. https://doi.org/10.1186/s13635-025-00203-9

Balash, D. G., Jr., Kim, D., Shaibekova, D., The George Washington University, Fainchtein, R. A., Sherr, M., Georgetown University, Aviv, A. J., & The George Washington University. (2021). Examining the examiners: Students’ privacy and security perceptions of online proctoring services. In Proceedings of the Seventeenth Symposium on Usable Privacy and Security. https://www.usenix.org/system/files/soups2021-balash.pdf

Barnett, V. and Lewis, T. (1994) Outliers in Statistical Data. 3rd Edition, John Wiley & Sons, Kluwer Academic Publishers, Boston/Dordrecht/London.

Carolus, A., Koch, M. J., Straka, S., Latoschik, M. E., & Wienrich, C. (2023). MAILS - Meta AI literacy scale: Development and testing of an AI literacy questionnaire based on well-founded competency models and psychological change- and meta-competencies. Computers in Human Behavior: Artificial Humans, 1(2), 100014. https://doi.org/10.1016/j.chbah.2023.100014

Cesana, B. M. (2018). What p-value must be used as the statistical significance. Biomedical Journal of Scientific & Technical Research, 6(3), 5310–5318. https://doi.org/10.26717/BJSTR.2018.06.00135

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed). Lawrence Erlbaum Associates.

Deisenrieder, V., Kubisch, S., Keller, L., & Stötter, J. (2020). Bridging the action gap by democratizing climate change education—The Case of k.i.d.Z.21 in the context of fridays for future. Sustainability, 12(5), 1748. https://doi.org/10.3390/su12051748

Field, A. (2018). Discovering Statistics Using IBM SPSS Statistics (5th ed.). Sage Publications Ltd.

Giannakos, M., Azevedo, R., Brusilovsky, P., Cukurova, M., Dimitriadis, Y., Hernandez-Leo, D., Järvelä, S., Mavrikis, M., & Rienties, B. (2025). The promise and challenges of generative AI in education. Behaviour and Information Technology, 44(11), 2518–2544. https://doi.org/10.1080/0144929X.2024.2394886

Gomathinayagam, I., Band, G., & Teltumbade, G. (2024). Artificial Intelligence’s (AI) role in higher education - challenges and applications. Academy of Marketing Studies Journal, 28(4), 1–9.

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (1998). Multivariate data analysis: Pearson College division (Seventh). Person: London, UK.

Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R. Springer. https://doi.org/10.1007/978-3-030-80519-7_7

Hellmann, M., Hernandez-Bocanegra, D. C., & Ziegler, J. (2022). Development of an instrument for measuring users’ perception of transparency in recommender systems. Joint Proceedings Ofthe ACM IUIWorkshops 2022, 3124, 156–165. https://ceur-ws.org/Vol-3124/paper17.pdf

Jeeyeon, S., & Sangmin, J. (2024). The role of consumers’ privacy awareness in the privacy calculus for iot services. International Journal of Human-Computer Interaction, 40(12), 3173–3184. https://doi.org/10.1080/10447318.2023.2184102

Kant, Immanuel. 1785. “First Section: Transition from the Common Rational Knowledge of Morals to the Philosophical”, Groundwork of the Metaphysic of Morals.

Kim, Yongnam. (2019). The causal structure of suppressor variables. Journal of Educational and Behavioral Statistics, 44(4), 367–389. https://doi.org/10.3102/1076998619825679

Kline, R. B. (2011). Principles and practice of structural equation modeling. In Guilford Publication. Guilford Press.

Korsgaard, C. M. (2012). Kant: Groundwork of the Metaphysics of Morals. In Cambridge Texts in the History of Philosophy (2nd ed.). Cambridge University Press. https://doi.org/DOI: 10.1017/CBO9780511919978

Kementarian Pendidikan Tinggi. (2024). Makro Institusi Pendidikan Tinggi: Statistik Pendidikan Tinggi 2024. https://mohe.gov.my/muat-turun/statistik/2024-4/1702-bab-1-makro-2024-update-pdf/file

Krejcie, R. V, & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607–610.

Leong, W. Y., & Zhang, J. B. (2025). Ethical design of ai for education and learning systems. ASM Science Journal, 20(1), 1–9. https://doi.org/10.32802/ASMSCJ.2025.1917

Li, B., Li, Q., Du, T., Liu, D., Yang, Q., Chen, T., Xiong, J., Peng, B., Ren, J., & Zhao, J. (2025). Research, application, and challenges of causal inference in industrial fault diagnosis: A survey. Engineering Applications of Artificial Intelligence, 158, 111376. https://doi.org/https://doi.org/10.1016/j.engappai.2025.111376

Liangru, Y., & Yi, L. (2022). Artificial intelligence decision-making transparency and employees’ trust: the parallel multiple mediating effect of effectiveness and discomfort. Behavioral Sciences, 12, 127. https://doi.org/10.3390/bs12050127

Maharmah, A. Al, Elfeky, A., Yacoub, R., Ibrahim, A., & Nemt-allah, M. (2025). Measuring ethical AI Use in higher education: Reliability and validity of the AI academic integrity scale for postgraduate students. International Journal of Innovative Research and Scientific Studies, 8(4), 707–715. https://doi.org/10.53894/ijirss.v8i4.7928

Mahusin, N., Sallehudin, H., & Satar, N. S. M. (2024). Malaysia public sector challenges of implementation of Artificial Intelligence (AI). IEEE Access, 12, 121035–121051. https://doi.org/10.1109/ACCESS.2024.3448311

Ma’rof, A. A., Dahamat Azam, M. N., & Rosnon, M. R. (2024). The impact of cultural values, emotional intelligence, social responsibility, and perceived social norms on helping behavior in malaysian young adults. International Journal of Academic Research in Business and Social Sciences, 14(12), 496–510. https://doi.org/10.6007/ijarbss/v14-i12/23999

Mat Yusoff, S., Mohamad Marzaini, A. F., Hao, L., Zainuddin, Z., & Basal, M. H. (2025). Understanding the role of AI in Malaysian higher education curricula: an analysis of student perceptions. Discover Computing, 28:62. https://doi.org/10.1007/s10791-025-09567-5

Ming, M., Davy, T. K. N., Zhichun, L., & Gary, K. W. W. (2025). Fostering responsible AI literacy: A systematic review of K-12 AI ethics education. Computers and Education: Artificial Intelligence, 8, 100422. https://doi.org/10.1016/j.caeai.2025.100422

Miskam, S., Sholehuddin, N., Mohd Shahwahid, F., Raja Abdul Aziz, T. N., & Mansor, N. (2023). Data privacy practices of private higher education institutions in malaysia: a preliminary study. Malaysian Journal of Information and Communication Technology, 8(2), 88–99. https://doi.org/10.53840/myjict8-2-99

Mohamad, N., Abd Karim Zamri, N., Roni, M., Ab Hadi, S. N. I., Nurr Sadikan, S. F., & Mahzan, S. (2025). Navigating AI Ethics in malaysian universities: addressing privacy, integrity, and bias. International Journal of Research and Innocation in Social Science, IX(1), 2451–2465. https://doi.org/10.47772/IJRISS

Mohd. Saman, H., Mohamed Noor, S., Mat Isa, C. M., Oh, C. L., & Narayanan, G. (2024). Embracing Artificial Intelligence as a Catalyst for Change in Reshaping Malaysian Higher Education in the Digital Era: A Literature Review. Proceedings of the International Conference on Innovation & Entrepreneurship in Computing, Engineering & Science Education (InvENT 2024), Advances in Computer Science Research 117, 633–643. https://doi.org/10.2991/978-94-6463-589-8_59

Nakarmi, S. S. (2024). Multi-collinearity in Research and Wayforward. Kaladarpan, 4(1), 85–91. https://doi.org/10.3126/kaladarpan.v4i1.62837

Nunnally, J. C. (1978). An overview of psychological measurement. Clinical Diagnosis of Mental Disorders: A Handbook, 97–146.

Oji, J., & Alordiah, C. O. (2024). Addressing ethical challenges in educational research: data privacy, informed consent, and ai bias in cybersecurity studies. Journal of Computing, Science &Technology, 2.

Radanliev, P. (2025). AI Ethics: Integrating Transparency, Fairness, and Privacy in AI Development. Applied Artificial Intelligence, 39:1. https://doi.org/10.1080/08839514.2025.2463722

Sekaran, U., & Bougie, R. (2016). Research Methods for Business: A Skill-Building Approach (7th ed.). Wiley. https://digilib.politeknik-pratama.ac.id/assets/dokumen/ebook/feb_f006f52b62a646e28c8c7870aa1112fbcd0c49ca_1650455622.pdf

Tabachnick, B. G., & Fidell, L. S. (2013). Using Multivariate Statistics. (6th ed.). Pearson.

Thelwall, M., & Kousha, K. (2025). Technology assisted research assessment: algorithmic bias and transparency issues. Aslib Journal of Information Management, 77(1), 175–190. https://doi.org/10.1108/AJIM-04-2023-0119

Vieriu, A. M., & Petrea, G. (2025). The impact of artificial intelligence on students’ learning experience. Education Sciences, 15(3), 343. https://doi.org/10.1007/978-3-031-71526-6_7

Wan Mokhtar, W. K. A., Ibrahim, A., Anas, N., Ahyar, & Sayekti, I. (2024). Ethical risks of using ChatGPT in higher education institutions in Malaysia. Masyarakat, Kebudayaan Dan Politik, 37(4), 432–445. https://doi.org/10.20473/mkp.V37I42024.432-445

Yunjo, A., Ji Hyun, Y., & James, S. (2025). Investigating the higher education institutions’ guidelines and policies regarding the use of generative AI in teaching, learning, research, and administration. International Journal of Educational Technology in Higher Education, 22(1). https://doi.org/10.1186/s41239-025-00507-3

Gomathinayagam, I., Band, G., & Teltumbade, G. (2024). Artificial Intelligence’s (AI) role in higher education - challenges and applications. Academy of Marketing Studies Journal, 28(4), 1–9.

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (1998). Multivariate data analysis: Pearson College division (Seventh). Person: London, UK.

Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R. Springer. https://doi.org/10.1007/978-3-030-80519-7_7

Hellmann, M., Hernandez-Bocanegra, D. C., & Ziegler, J. (2022). Development of an instrument for measuring users’ perception of transparency in recommender systems. Joint Proceedings Ofthe ACM IUIWorkshops 2022, 3124, 156–165. https://ceur-ws.org/Vol-3124/paper17.pdf

Jeeyeon, S., & Sangmin, J. (2024). The role of consumers’ privacy awareness in the privacy calculus for iot services. International Journal of Human-Computer Interaction, 40(12), 3173–3184. https://doi.org/10.1080/10447318.2023.2184102

Kant, Immanuel. 1785. “First Section: Transition from the Common Rational Knowledge of Morals to the Philosophical”, Groundwork of the Metaphysic of Morals.

Kim, Yongnam. (2019). The causal structure of suppressor variables. Journal of Educational and Behavioral Statistics, 44(4), 367–389. https://doi.org/10.3102/1076998619825679

Kline, R. B. (2011). Principles and practice of structural equation modeling. In Guilford Publication. Guilford Press.

Korsgaard, C. M. (2012). Kant: Groundwork of the Metaphysics of Morals. In Cambridge Texts in the History of Philosophy (2nd ed.). Cambridge University Press. https://doi.org/DOI: 10.1017/CBO9780511919978

Kementarian Pendidikan Tinggi. (2024). Makro Institusi Pendidikan Tinggi: Statistik Pendidikan Tinggi 2024. https://mohe.gov.my/muat-turun/statistik/2024-4/1702-bab-1-makro-2024-update-pdf/file

Krejcie, R. V, & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607–610.

Leong, W. Y., & Zhang, J. B. (2025). Ethical design of ai for education and learning systems. ASM Science Journal, 20(1), 1–9. https://doi.org/10.32802/ASMSCJ.2025.1917

Li, B., Li, Q., Du, T., Liu, D., Yang, Q., Chen, T., Xiong, J., Peng, B., Ren, J., & Zhao, J. (2025). Research, application, and challenges of causal inference in industrial fault diagnosis: A survey. Engineering Applications of Artificial Intelligence, 158, 111376. https://doi.org/https://doi.org/10.1016/j.engappai.2025.111376

Liangru, Y., & Yi, L. (2022). Artificial intelligence decision-making transparency and employees’ trust: the parallel multiple mediating effect of effectiveness and discomfort. Behavioral Sciences, 12, 127. https://doi.org/10.3390/bs12050127

Maharmah, A. Al, Elfeky, A., Yacoub, R., Ibrahim, A., & Nemt-allah, M. (2025). Measuring ethical AI Use in higher education: Reliability and validity of the AI academic integrity scale for postgraduate students. International Journal of Innovative Research and Scientific Studies, 8(4), 707–715. https://doi.org/10.53894/ijirss.v8i4.7928

Mahusin, N., Sallehudin, H., & Satar, N. S. M. (2024). Malaysia public sector challenges of implementation of Artificial Intelligence (AI). IEEE Access, 12, 121035–121051. https://doi.org/10.1109/ACCESS.2024.3448311

Ma’rof, A. A., Dahamat Azam, M. N., & Rosnon, M. R. (2024). The impact of cultural values, emotional intelligence, social responsibility, and perceived social norms on helping behavior in malaysian young adults. International Journal of Academic Research in Business and Social Sciences, 14(12), 496–510. https://doi.org/10.6007/ijarbss/v14-i12/23999

Mat Yusoff, S., Mohamad Marzaini, A. F., Hao, L., Zainuddin, Z., & Basal, M. H. (2025). Understanding the role of AI in Malaysian higher education curricula: an analysis of student perceptions. Discover Computing, 28:62. https://doi.org/10.1007/s10791-025-09567-5

Ming, M., Davy, T. K. N., Zhichun, L., & Gary, K. W. W. (2025). Fostering responsible AI literacy: A systematic review of K-12 AI ethics education. Computers and Education: Artificial Intelligence, 8, 100422. https://doi.org/10.1016/j.caeai.2025.100422

Miskam, S., Sholehuddin, N., Mohd Shahwahid, F., Raja Abdul Aziz, T. N., & Mansor, N. (2023). Data privacy practices of private higher education institutions in malaysia: a preliminary study. Malaysian Journal of Information and Communication Technology, 8(2), 88–99. https://doi.org/10.53840/myjict8-2-99

Mohamad, N., Abd Karim Zamri, N., Roni, M., Ab Hadi, S. N. I., Nurr Sadikan, S. F., & Mahzan, S. (2025). Navigating AI Ethics in malaysian universities: addressing privacy, integrity, and bias. International Journal of Research and Innocation in Social Science, IX(1), 2451–2465. https://doi.org/10.47772/IJRISS

Mohd. Saman, H., Mohamed Noor, S., Mat Isa, C. M., Oh, C. L., & Narayanan, G. (2024). Embracing Artificial Intelligence as a Catalyst for Change in Reshaping Malaysian Higher Education in the Digital Era: A Literature Review. Proceedings of the International Conference on Innovation & Entrepreneurship in Computing, Engineering & Science Education (InvENT 2024), Advances in Computer Science Research 117, 633–643. https://doi.org/10.2991/978-94-6463-589-8_59

Nakarmi, S. S. (2024). Multi-collinearity in Research and Wayforward. Kaladarpan, 4(1), 85–91. https://doi.org/10.3126/kaladarpan.v4i1.62837

Nunnally, J. C. (1978). An overview of psychological measurement. Clinical Diagnosis of Mental Disorders: A Handbook, 97–146.

Oji, J., & Alordiah, C. O. (2024). Addressing ethical challenges in educational research: data privacy, informed consent, and ai bias in cybersecurity studies. Journal of Computing, Science &Technology, 2.

Radanliev, P. (2025). AI Ethics: Integrating Transparency, Fairness, and Privacy in AI Development. Applied Artificial Intelligence, 39:1. https://doi.org/10.1080/08839514.2025.2463722

Sekaran, U., & Bougie, R. (2016). Research Methods for Business: A Skill-Building Approach (7th ed.). Wiley. https://digilib.politeknik-pratama.ac.id/assets/dokumen/ebook/feb_f006f52b62a646e28c8c7870aa1112fbcd0c49ca_1650455622.pdf

Tabachnick, B. G., & Fidell, L. S. (2013). Using Multivariate Statistics. (6th ed.). Pearson.

Thelwall, M., & Kousha, K. (2025). Technology assisted research assessment: algorithmic bias and transparency issues. Aslib Journal of Information Management, 77(1), 175–190. https://doi.org/10.1108/AJIM-04-2023-0119

Vieriu, A. M., & Petrea, G. (2025). The impact of artificial intelligence on students’ learning experience. Education Sciences, 15(3), 343. https://doi.org/10.1007/978-3-031-71526-6_7

Wan Mokhtar, W. K. A., Ibrahim, A., Anas, N., Ahyar, & Sayekti, I. (2024). Ethical risks of using ChatGPT in higher education institutions in Malaysia. Masyarakat, Kebudayaan Dan Politik, 37(4), 432–445. https://doi.org/10.20473/mkp.V37I42024.432-445

Yunjo, A., Ji Hyun, Y., & James, S. (2025). Investigating the higher education institutions’ guidelines and policies regarding the use of generative AI in teaching, learning, research, and administration. International Journal of Educational Technology in Higher Education, 22(1). https://doi.org/10.1186/s41239-025-00507-3