Abstract
Artificial intelligence is increasingly being adopted in higher education to support teaching, learning, administration, quality assurance, and institutional planning. However, much of the current discussion remains focused on adoption, efficiency, and technological capability, with less attention to the interpretive and governance conditions required for responsible institutional use. This article addresses that gap by developing a Buddhist interpretive framework for AI governance in higher education. Drawing on a qualitative study based on semi-structured individual interviews with 16 key informants, a focus group discussion with 9 additional participants, and document analysis of relevant academic and policy literature, the study explores how AI is understood, justified, and governed within university contexts. Data were triangulated across all three sources to strengthen interpretive validity. The analysis identifies four major themes: AI as an institutional governance project; AI as a system-shaping force across core university functions; responsible AI as dependent on enabling conditions and safeguards; and an interpretive logic among participants that aligns with the four dimensions of Patisambhida. Rather than treating Buddhist thought as a symbolic ethical add-on, the article reinterprets Patisambhida as an interpretive governance architecture for AI: Attha as purpose governance, Dhamma as principle governance, Nirutti as communicative governance, and Patibhana as judgment governance. Based on this synthesis, the study proposes a Buddhist Interpretive Governance Framework that may help explain how universities can move from AI adoption toward human-centered AI governance.
- Acar, E., Yigit, F., & Deiri, Y. (2025). A focused review of artificial intelligence in education: Evolution and challenges. Journal of Interdisciplinary Research in Artificial Intelligence and Society, 1(1), Article 3. https://doi.org/10.20897/jirais/17640
- Baker, R. S., & Hawn, A. (2022). Algorithmic bias in education. International Journal of Artificial Intelligence in Education, 32(4), 1052–1092. https://doi.org/10.1007/s40593-021-00285-9
- Chaimongkol, T., & Rattanakantadilok, G. (2026). Female representation in the Thai boys' love industry: The intersection of privilege and oppression. Feminist Encounters: A Journal of Critical Studies in Culture and Politics, 10(1), Article 31. https://doi.org/10.20897/femenc/18174
- Crawford, K. (2021). Atlas of AI: Power, politics, and the planetary costs of artificial intelligence. Yale University Press.
- Dalgalıdere, S. (2025). Generative artificial intelligence in crisis journalism: A comparative analysis of ChatGPT and Gemini news texts. ISophos: International Journal of Information, Technology and Philosophy, 8(15), 1–11.
- Dignum, V. (2019). Responsible artificial intelligence: How to develop and use AI in a responsible way. Springer. https://doi.org/10.1007/978-3-030-30371-6
- Floridi, L., & Cowls, J. (2019). A unified framework of five principles for AI in society. Harvard Data Science Review, 1(1). https://doi.org/10.1162/99608f92.8cd550d1
- Gjini, T. W., & Hernandez-Gantes, V. M. (2025). Who gets to intern? Demographic and institutional predictors of internship participation among international students. European Journal of Education & Language Review, 1(1), Article 1. https://doi.org/10.20897/ejelr/17312
- Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Buckingham Shum, S., Santos, O. C., Rodrigo, M. T., Cukurova, M., Bittencourt, I. I., & Koedinger, K. R. (2022). Ethics of AI in education: Towards a community-wide agenda. International Journal of Artificial Intelligence in Education, 32(3), 504–526. https://doi.org/10.1007/s40593-021-00239-1
- Ismayil, Z., Jafarov, A., Adil, G., Soltanova, A., Mansimova, K., Alishanova, A., Gundogdu, S., Hasanova, N., Aliyev, S., Ahmadov, H., Amrahov, Z., & Nuri, A. (2026). Faculty perceptions of generative AI in Azerbaijani higher education. European Journal of STEM Education, 11(1), Article 21. https://doi.org/10.20897/ejsteme/18310
- Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), 389–399. https://doi.org/10.1038/s42256-019-0088-2
- Katz, N. (2026). Digital inequality in context: A socio-technical analysis of Arab students' remote learning in Israel. Asia Pacific Journal of Education and Society, 14(1), Article 6. https://doi.org/10.20897/apjes/17975
- Lee, J., Wang, S., & Esposito, A. G. (2025). Content analysis of college student perceptions: Mental health-related support from generative AI versus faculty mentors. American Journal of Qualitative Research, 9(4), 70–100. https://doi.org/10.29333/ajqr/16815
- Muciaccia, T., & Macchia, L. (2025). Artificial intelligence, collective intelligence, and human experience: A socio-economic and ontological analysis. Journal of Interdisciplinary Research in Artificial Intelligence and Society, 1(1), Article 2. https://doi.org/10.20897/jirais/17618
- Sarkar, R. (2025). A review of human-centered AI: A multidisciplinary perspective for policy-makers, auditors, and users. Journal of Interdisciplinary Research in Artificial Intelligence and Society, 1(1), Article 1. https://doi.org/10.20897/jirais/17534
- Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. Polity Press.
- Shneiderman, B. (2022). Human-centered AI. Oxford University Press. https://doi.org/10.1093/oso/ 9780192845290.001.0001
- Sultan, Y., Dautova, G., & Dalle, J. (2025). Examining the relationship among artificial intelligence literacy, cultural literacy, and intercultural communication proficiency of philology students. Journal of Ethnic and Cultural Studies, 12(5), 345–362. https://doi.org/10.29333/ejecs/2839
- UNESCO. (2021). Recommendation on the ethics of artificial intelligence. United Nations Educational, Scientific and Cultural Organization. https://unesdoc.unesco.org/ark:/48223/pf0000381137
- Williamson, B., Eynon, R., & Potter, J. (2020). Pandemic politics, pedagogies and practices: Digital technologies and distance education during the coronavirus emergency. Learning, Media and Technology, 45(2), 107–114. https://doi.org/10.1080/17439884.2020.1761641
- 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), Article 39. https://doi.org/10.1186/s41239-019-0171-0
APA 7th edition
In-text citation: (Tuanpusa et al., 2026)
Reference: Tuanpusa, S., Sritragarn, T., Kaewthongyai, Y., & Tuenpusa, P. (2026). From AI adoption to AI governance: Developing a Buddhist interpretive framework for higher education.
Journal of Interdisciplinary Research in Artificial Intelligence and Society, 2(1), Article 3.
https://doi.org/10.20897/jirais/18573
AMA 10th edition
In-text citation: (1), (2), (3), etc.
Reference: Tuanpusa S, Sritragarn T, Kaewthongyai Y, Tuenpusa P. From AI adoption to AI governance: Developing a Buddhist interpretive framework for higher education.
Journal of Interdisciplinary Research in Artificial Intelligence and Society. 2026;2(1), 3.
https://doi.org/10.20897/jirais/18573
Chicago
In-text citation: (Tuanpusa et al., 2026)
Reference: Tuanpusa, Svangnabha, Thongdee Sritragarn, Yudthavee Kaewthongyai, and Pongpith Tuenpusa. "From AI adoption to AI governance: Developing a Buddhist interpretive framework for higher education".
Journal of Interdisciplinary Research in Artificial Intelligence and Society 2026 2 no. 1 (2026): 3.
https://doi.org/10.20897/jirais/18573
Harvard
In-text citation: (Tuanpusa et al., 2026)
Reference: Tuanpusa, S., Sritragarn, T., Kaewthongyai, Y., and Tuenpusa, P. (2026). From AI adoption to AI governance: Developing a Buddhist interpretive framework for higher education.
Journal of Interdisciplinary Research in Artificial Intelligence and Society, 2(1), 3.
https://doi.org/10.20897/jirais/18573
MLA
In-text citation: (Tuanpusa et al., 2026)
Reference: Tuanpusa, Svangnabha et al. "From AI adoption to AI governance: Developing a Buddhist interpretive framework for higher education".
Journal of Interdisciplinary Research in Artificial Intelligence and Society, vol. 2, no. 1, 2026, 3.
https://doi.org/10.20897/jirais/18573
Vancouver
In-text citation: (1), (2), (3), etc.
Reference: Tuanpusa S, Sritragarn T, Kaewthongyai Y, Tuenpusa P. From AI adoption to AI governance: Developing a Buddhist interpretive framework for higher education. Journal of Interdisciplinary Research in Artificial Intelligence and Society. 2026;2(1):3.
https://doi.org/10.20897/jirais/18573