| Artificial intelligence, as a principal driver of transformation in recent years and those to come, has redefined the role of universities in global competition and in the provision of scientific and educational services. Aiming to design a strategic roadmap for reconfiguring university culture in this context, this article examines changes in norms, roles, and customary practices in higher education. This transformation rests on three pillars—transformed leadership, faculty readiness, and access to advanced infrastructures—and has been reinforced by the post COVID acceleration of digital transformation in higher education. Methodologically, the study adopts a conceptual synthesis approach and proposes a staged model to explain cultural transformation. The model comprises three successive stages: first, an organizational flexibility stage that emphasizes local meanings and actor networks; second, an institutional consolidation stage in which rules and procedures are stabilized; and third, a technological impetus stage in which data driven infrastructures and emerging information architectures play a decisive role in shaping organizational culture. Across all stages, mediating and moderating mechanisms—including transparent data governance, algorithmic accountability, enhanced digital competence and literacy among faculty members, and equitable access—play a pivotal role. Building on this model, the article proposes an operational, stage based roadmap for policymaking, implementation, and evaluation, organized around three axes: strengthening transparent and effective data governance, enhancing the digital competence of all university actors, and reducing inequalities in access to infrastructures and opportunities in Iranian universities. The roadmap is designed to support the responsible adoption of AI while preventing the reproduction of existing educational inequalities and fostering a culture of accountability, equity, and lifelong learning. |
- Akinwumi, M. (2025, May). AI governance: Overcoming policy barriers to fairness and privacy. Connecticut Law Review, 57(4), 1161-1201. Retrieved from https://digitalcommons.lib.uconn.edu/law_review
- Alenezi, M. (2021). Digital transformation in higher education: Challenges and opportunities. International Journal of Educational Technology in Higher Education, 18(1), 1-15.
- Asghari, M. (2021). Barriers to digital transformation in Iranian universities: A structural analysis. Journal of Higher Education Policy and Management, 43(2), 156-173.
- Beyond the States. (2025, June 11). College in Europe vs U.S. (What's actually different). Retrieved from https://beyondthestates.com/college-in-europe-vs-us/
- Carnegie Learning. (2020). Adaptive learning research outcomes. Pittsburgh: Carnegie Learning Inc.
- DCU (Dublin City University). (2025, October 13). AI bias in criminal justice can be reduced through multi-stage approach. Retrieved from https://www.dcu.ie/research/news/2025/oct/
- Digital Transformation Skills. (2023). Building digital capabilities in higher education institutions. London: British Council.
- EDUCAUSE. (2024, February 4). Digital transformation 2.0: The age of AI. Educause Review. Retrieved from https://er.educause.edu/articles/2024/2/digital-transformation-20-the-age-of-ai
- EDUCAUSE. (2025, June 23). AI ethical guidelines. Retrieved from https://library.educause.edu/resources/2025/6/
- Ellucian. (2024, October 21). Ellucian's AI survey of higher education professionals. Retrieved from https://www.ellucian.com/newsroom/
- Ellucian. (2025, September 11). AI in higher ed: What's next for middle east universities. Retrieved from https://www.ellucian.com/en-gb/blog/
- European Journal of Education. (2025, August 9). Higher education AI policies—A document analysis of university practices in Sweden. Retrieved from https://uu.diva-portal.org/
- European University Association. (2023). Universities and Artificial Intelligence: Readiness and Practice. Brussels.
- Forbes. (2025, September 2). AI is everywhere in higher ed. Where's the AI governance? Retrieved from https://www.forbes.com/sites/avivalegatt/2025/09/03/ai-is-everywhere-in-higher-ed-wheres-the-ai-governance/
- Gkrimpizi, A., Peristeras, V., & Magnisalis, I. (2023). A framework for digital transformation in universities. Education and Information Technologies, 28(3), 2891-2917.
- Hart, K., & Mok, R. (2023). AI in Higher Education: Current Trends and Future Prospects. Journal of Educational Technology & Society, 26(2), 156-172.
- Hilbert, M. (2022). Digital technology and social change: The digital transformation of society from a historical perspective. Dialogues in Clinical Neuroscience, 22(2), 189-203.
- Indiana Law Journal. (2025, May 31). The overstated cost of AI fairness in criminal justice. Indiana Law Journal, 100(4), 1431. Retrieved from https://www.repository.law.indiana.edu/ilj/
- Inspera. (2025, April 16). Examples of ethical AI for educators in higher education. Retrieved from https://inspera.com/ai/examples-of-ethical-ai-for-educators/
- Kumar, V., & Raman, R. (2022). Data-driven decision making in higher education: Opportunities and challenges. International Journal of Educational Management, 36(5), 789-808.
- Liaison Education. (2025, April 28). AI-driven decision making: Empowering higher ed leaders to thrive. Retrieved from https://www.liaisonedu.com/resources/blog/
- Loh, C. Y. R., & Teo, T. C. (2017). Understanding Asian students learning styles, cultural influence and learning strategies. Journal of Education & Social Policy, 4(1), 194-210.
- MacGregor, K. (2023). African universities struggle with AI integration challenges. University World News, 45(3), 18-24.
- Marginson, S. (2016). Higher education and public good. Higher Education Quarterly, 70(2), 312-335.
- NCBI. (2022, September 8). Change management: From theory to practice. Retrieved from https://pmc.ncbi.nlm.nih.gov/articles/
- Pisica, A. I., Miron, C., & Socoliuc, G. (2023). Institutional mechanisms for AI adoption in European universities. Higher Education Quarterly, 77(4), 512-534.
- Policy Options. (2025, September 18). Canada needs a national strategy for generative AI in higher education. Retrieved from https://policyoptions.irpp.org/2025/09/ai-higher-ed/
- Readings, B. (1996). The university in ruins. Cambridge: Harvard University Press.
- Robert, L. (2024). Organizational change and resistance: A study of digital transformation in higher education. Higher Education Quarterly, 78(1), 23-45.
- Schein, E. H. (2010). Organizational culture and leadership (4th ed.). Jossey-Bass.
- Schwab, K. (2016). The Fourth Industrial Revolution. World Economic Forum.
- Stensaker, B. (2015). Institutional identity as a concept for understanding university dynamics. Higher Education, 69(1), 103-115.
- Thornton, M. (2020). Student expectations and learning in the digital age. Journal of Educational Technology & Society, 23(4), 78-95.
- Tierney, W. G. (1988). Organizational culture in higher education: Defining the essentials. The Journal of Higher Education, 59(1), 2-21.
- Trowler, P. (2008). Cultures and change in higher education: Theories and practices. Basingstoke: Palgrave Macmillan.
- Watermark Insights. (2025, September 21). How to implement data‑driven decision‑making in higher education. Retrieved from https://www.watermarkinsights.com/resources/blog/
- Zeide, E. (2019). The Structural Problem of Transparency in Algorithmic Accountability. Fordham L. Rev., 88, 1383-1430.
- Zwetsloot, R. (2021). Keeping Top AI Talent in the United States. Center for Security and Emerging Technology.
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