AI and Qur’anic Interpretation: Exploring the Ethical and Epistemological Boundaries of Artificial Intelligence in Understanding the Qur’an

The rapid development of Artificial Intelligence (AI) has significantly influenced religious studies, particularly in the analysis and interpretation of sacred texts. This study critically examines the role of AI in Qur’anic interpretation by addressing its epistemic capabilities, ethical limitations, and claims to interpretive authority. Employing a qualitative, literature-based research design, this study analyzes peer-reviewed scholarship on AI and religion, computational hermeneutics, natural language processing of sacred texts, and algorithmic bias, alongside classical and contemporary works in Islamic epistemology and Qur’anic exegesis. The findings indicate that while AI demonstrates high proficiency in linguistic processing, semantic consistency, and structural analysis of religious texts, it lacks epistemic understanding, moral intentionality, and ontological subjectivity. From the perspective of Islamic epistemology, knowledge is inseparable from consciousness, ethical responsibility, and interpretive accountability—dimensions that AI cannot possess. Moreover, algorithmic bias and the risk of decontextualization further challenge the use of AI as an autonomous interpretive authority in religious contexts. This study argues that AI should be positioned as an instrumental analytical tool rather than a subject of interpretation in Qur’anic exegesis. Its primary contribution lies in articulating a clear epistemological boundary between computational processing and hermeneutical understanding, thereby offering a critical framework for the ethical and responsible integration of AI within Islamic studies and religious scholarship more broadly.

How to Cite
Alrumayh, S. (2025). AI and Qur’anic Interpretation: Exploring the Ethical and Epistemological Boundaries of Artificial Intelligence in Understanding the Qur’an. Al Furqan: Jurnal Ilmu Al Quran Dan Tafsir, 8(2), 223-239. https://doi.org/10.58518/alfurqan.v8i2.4243

Safa Alrumayh

University of Zawia, Libya

Al-Attas, M. N. (1993). The concept of education in Islam (pp. 19-33). Kuala Lumpur: Muslim Youth Movement of Malaysia.

al-Ghazali, A. H. (2005). Ihya’ ’Ulum Ad-Din. Dar Ibn Hazm.

Al-Razi, F. (1981). Mafatih al-Ghayb. Dar al-Fikr.

Al-Thabari, I. J. (2001). Jami’ al-Bayan ’an Ta’wil Ay al-Qur’an. Dar Hijr li al-Thaba’ah wa al-Nashr wa al-Tawzi’ wa al-I’lan.

AlHasani, H., Saad, S., & Kassim, J. (2018). Classification of encouragement (Targhib) and warning (Tarhib) using sentiment analysis on classical arabic. International Journal on Advanced Science, Engineering and Information Technology, 8(4–2), 1721–1727. https://doi.org/10.18517/ijaseit.8.4-2.6800

Ali, S. I., Albadoo, S. F., & Al Mubarak, M. (2025). Ethical Ramifications and Remedial Approaches on Bias in Artificial Intelligence. In Studies in Systems, Decision and Control (Vol. 237, pp. 95–108). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-86708-8_8

Azhar, M. H. M., Bakri, M. F. M., Ahmad, K., & Rosele, M. I. (2025). Ethics and Limits of Artificial Intelligence (AI) in Quranic Exegesis According to the Epistemological Framework of Islamic Knowledge. Quranica, 17(2), 97–124. https://www.scopus.com/inward/record.uri?eid=2-s2.0-105018233406&partnerID=40&md5=2b4db6dfe95e93ec70f563c9c3f2d622

Beirade, F., Azzoune, H., & Zegour, D. E. (2021). Semantic query for Quranic ontology. Journal of King Saud University - Computer and Information Sciences, 33(6), 753–760. https://doi.org/10.1016/j.jksuci.2019.04.005

Alkhouri, K. I. (2024). The Role of Artificial Intelligence in the Study of the Psychology of Religion. Religions, 15(3). https://doi.org/10.3390/rel15030290

Chandra, R., & Kulkarni, V. (2022). Semantic and Sentiment Analysis of Selected Bhagavad Gita Translations Using BERT-Based Language Framework. IEEE Access, 10, 21291–21315. https://doi.org/10.1109/ACCESS.2022.3152266

Chandra, R., Tiwari, A., Jain, N., & Badhe, S. (2024). Large Language Models for Metaphor Detection: Bhagavad Gita and Sermon on the Mount. IEEE Access, 12, 84452–84469. https://doi.org/10.1109/ACCESS.2024.3411060

Chavanayarn, S. (2023). Navigating Ethical Complexities Through Epistemological Analysis of ChatGPT. Bulletin of Science, Technology and Society, 43(3–4), 105–114. https://doi.org/10.1177/02704676231216355

Demircigil, B. (2025). The Conceptualization of Jurisprudential Exegesis as the Intersection of Tafsir and Fiqh: A Critical Approach. Religions, 16(2). https://doi.org/10.3390/rel16020254

Fitryansyah, M. A., & Fauziah, F. N. (2024). BRIDGING TRADITION AND TECHNOLOGY: AI IN THE INTERPRETATION OF NUSANTARA RELIGIOUS MANUSCRIPTS. Jurnal Lektur Keagamaan, 22(2), 317–346. https://doi.org/10.31291/jlka.v22i2.1247

Fuenmayor, D., & Benzmüller, C. (2019). A computational-hermeneutic approach for conceptual explicitation. In Studies in Applied Philosophy, Epistemology and Rational Ethics (Vol. 49, pp. 441–469). Springer International Publishing. https://doi.org/10.1007/978-3-030-32722-4_25

Iqbal, M. (2000). Islam and modern science: Formulating the questions. Islamic studies, 39(4), 517-570.

Kamali, M. H. (2019). Principles and Philosophy of Punishment in Islamic Law with Special Reference to Malaysia. ICR Journal, 10(1), 9-20.

Kurata, L., Ayanwale, M. A., Molefi, R. R., & Sanni, T. (2025). Teaching religious studies with artificial intelligence: A qualitative analysis of Lesotho secondary schools teachers’ perceptions. International Journal of Educational Research Open, 8. https://doi.org/10.1016/j.ijedro.2024.100417

Leavy, S., Meaney, G., Wade, K., & Greene, D. (2020). Mitigating gender bias in machine learning data sets. In B. L., F. S., M. M., & S. G. (Eds.), Communications in Computer and Information Science: Vol. 1245 CCIS (pp. 12–26). Springer. https://doi.org/10.1007/978-3-030-52485-2_2

Malik, S. A. (2023). Artificial Intelligence and Islamic Thought: Two Distinctive Challenges. Journal of Islamic and Muslim Studies, 8(2), 108–115. https://doi.org/10.2979/jims.00020

Mandal, S., & Hawamdeh, M. M. K. (2025). Digital well-being and AI: Navigating the intersection between technology and mental health. In Digital Citizenship and the Future of AI Engagement, Ethics, and Privacy (pp. 111–132). IGI Global. https://doi.org/10.4018/979-8-3693-9015-3.ch004

Mauluddin, M. (2024). Kontribusi Artificial Intelligence (AI) pada studi al Quran di era digital; peluang dan tantangan. Madinah: Jurnal Studi Islam, 11(1), 99-113.

Mohd Yousof, N. M., Selamat, A., Shaffiei, Z. A., Ibrahim, S. N. K. A., Burhanuddin, L., & Fujita, H. (2025). An Intelligent NLP-Based Framework for Digital Scripts Concordance and Semantic Exploration. In F. H., H.-M. A., & W. Y. (Eds.), Frontiers in Artificial Intelligence and Applications (Vol. 411, pp. 457–467). IOS Press BV. https://doi.org/10.3233/FAIA250545

Papakostas, C. (2025). Artificial Intelligence in Religious Education: Ethical, Pedagogical, and Theological Perspectives. Religions, 16(5). https://doi.org/10.3390/rel16050563

Putrawan, B. K. (2025). From Prayer to Data: The Transformation of Theology in the Age of Artificial Intelligence and its Implications for Religious Practice. Transformation. https://doi.org/10.1177/02653788241312229

Revathy, G., Nandhini, T., Brem Kumar, M., & Senthilvadivu, S. (2025). Ethical Implications and Bias Mitigation in Machine Learning Algorithms. In B. A., D. S., C. A., & P. T. (Eds.), Lecture Notes in Networks and Systems: Vol. 1410 LNNS (pp. 317–327). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-96-6303-3_23

Rohra, N., & Prasad Shukla, S. S. (2025). Sentiment Analysis of Spiritual Teachings: Ensemble Learning Applied to Twitter Religious Text and Bhagavad Gita. Proceedings of IEEE International Conference on Signal Processing,Computing and Control, 960–967. https://doi.org/10.1109/ISPCC66872.2025.11039323

Sati, A., Halim, A., Nasution, A. H., & Ridwan, M. (2025). The Digital Transformation of Tafsir and Its Implications for Islamic Legal Derivation in the Contemporary Era. MILRev: Metro Islamic Law Review, 4(1), 389–415. https://doi.org/10.32332/milrev.v4i1.10425

Sawalha, M., Al-Shargi, F., Yagi, S., AlShdaifat, A. T., Hammo, B., Belajeed, M., & Al-Ogaili, L. R. (2025). Morphologically-analyzed and syntactically-annotated Quran dataset. Data in Brief, 58. https://doi.org/10.1016/j.dib.2024.111211

Shin, D., & Shin, E. Y. (2023). Data’s Impact on Algorithmic Bias. Computer, 56(6), 90–94. https://doi.org/10.1109/MC.2023.3262909

Srivash, A., Chadha, S., Chauhan, R., & Arun, K. G. (2025). Ethical Implication of AI Decision-Making in Various Sectors. In Advances in AI for Financial, Cyber, and Healthcare Analytics: A Multidisciplinary Approach (pp. 62–73). Bentham Science Publishers. https://doi.org/10.2174/9798898810542125010007

Supena, I. (2024). Epistemology of Tafsīr, Ta’wīl, and Hermeneutics: Towards an Integrative Approach. Journal of Islamic Thought and Civilization, 14(1), 121–136. https://doi.org/10.32350/jitc.141.08

Zhang, J., Song, W., & Liu, Y. (2025). Cognitive bias in generative AI influences religious education. Scientific Reports, 15(1). https://doi.org/10.1038/s41598-025-99121-6