Integration of Artificial Intelligence in the Science of Tafsīr: A Critical Analysis of Opportunities and Challenges for Contemporary Quranic Studies

Authors

  • Yazdan Kabir Charles Sturt University, Australia Author
  • Klapdor Hammond Charles Sturt University, Australia Author
  • Ernest Drennen Charles Sturt University, Australia Author
  • Sarah Jemali Charles Sturt University, Australia Author
  • Rekha Dastyari Western Sydney University, Australia Author

DOI:

https://doi.org/10.64691/3zsxrs39

Keywords:

Artificial Intelligence, Science of Interpretation, Epistemology of Interpretation, Digital Hermeneutics, Al-Quran

Abstract

The integration of artificial intelligence into Quranic studies marks a significant transformation in contemporary interpretive practices. However, existing studies remain dominated by technical and normative approaches, lacking adequate epistemological-critical analysis. This situation raises fundamental issues regarding the relationship between algorithmic logic and the interpretive principles of tafsīr, which are contextual, reflective, and historical. This study aims to critically analyze the epistemological opportunities and challenges of AI integration into tafsīr and to formulate the boundaries and epistemic functions of AI within contemporary tafsīr methodology. The study uses a qualitative-analytical approach with a critical literature study design, drawing on classical and modern tafsīr literature, the philosophy of science, and cutting-edge digital humanities studies. The analysis is conducted through a hermeneutical-critical reading and a conceptual-comparative analysis of claims of objectivity in technology and interpretive practices. The results show that AI has the potential to strengthen tafsīr studies by processing large corpora, mapping intertextuality across tafsīrs, and systematically identifying linguistic patterns in the Quran, thereby opening up previously difficult-to-reach analytical horizons. However, this study also uncovered three major challenges: the tendency to positivize meaning due to the reduction of text to data, the neglect of the historical-social context of revelation, and the reification of algorithmic output as interpretive authority. These findings highlight the structural tension between claims of AI objectivity and the interpretive nature of tafsīr. The study concludes that integrating AI should be positioned as a supporting instrument guided by critical reasoning in tafsīr to enrich contemporary Quranic studies without eroding its epistemological complexity.

Author Biographies

  • Yazdan Kabir, Charles Sturt University, Australia

    Centre for Islamic Studies and Civilisation

  • Klapdor Hammond, Charles Sturt University, Australia

    Centre for Islamic Studies and Civilisation

  • Ernest Drennen, Charles Sturt University, Australia

    Artificial Intelligence and Cyber Futures Centre

  • Sarah Jemali, Charles Sturt University, Australia

    Centre for Islamic Studies and Civilisation

  • Rekha Dastyari, Western Sydney University, Australia

    Islamic Studies Major

References

Abu Zayd, N. H. (2004). Text, Authority, and Community: Essays in Quranic Hermeneutics. Leiden: Brill.

Al-Qaṭṭān, M. (1973). Mabāḥith fī ʻUlūm al-Qurʻān. Beirut: Mu’assasah al-Risālah.

Al-Suyūṭī, Jalāl al-Dīn. (1974). al-Itqān fī ʻUlūm Al-Qurʻān. Egypt: al-Hay’ah al-Miṣriyyah.

Al-Dhahabī, M. al-S. Ḥusayn. (1976). Al-Tafsīr wa al-Mufassirūn. Cairo: Maktabah Wahbah.

Al-Zarkashī, ‘Abd Allah ibn B. (1957). al-Burhān fī ‘Ulūm Al-Qurʻān. Beirut: Dār al-Ma’rifah.

Alshammeri, M., Atwell, E., & Alsalka, M. ammar. (2021). Detecting Semantic-based Similarity Between Verses of The Quran with Doc2vec. Procedia Computer Science, 189, 351–358. https://doi.org/10.1016/j.procs.2021.05.104 DOI: https://doi.org/10.1016/j.procs.2021.05.104

Bashir, M. H., Azmi, A. M., Nawaz, H., Zaghouani, W., Diab, M., Al-Fuqaha, A., & Qadir, J. (2023). Arabic natural language processing for Qur’anic research: a systematic review. Artificial Intelligence Review, 56(7), 6801–6854. https://doi.org/10.1007/s10462-022-10313-2 DOI: https://doi.org/10.1007/s10462-022-10313-2

Bhat, A. M., & Bisati, A. A. (2025). Rationality in the Qur’an: Integrating Reason and Revelation for Contemporary Islamic Education. Dirasah International Journal of Islamic Studies, 3(1), 1–17. https://doi.org/10.59373/drs.v3i1.40 DOI: https://doi.org/10.59373/drs.v3i1.40

Biddle, J. B. (2022). On Predicting Recidivism: Epistemic Risk, Tradeoffs, and Values in Machine Learning. Canadian Journal of Philosophy, 52(3), 321–341. https://doi.org/10.1017/can.2020.27 DOI: https://doi.org/10.1017/can.2020.27

Dandelet, S. (2024). Epistemic Rationality and the Value of Truth. Philosophical Review, 133(4), 329–365. https://doi.org/10.1215/00318108-11494797 DOI: https://doi.org/10.1215/00318108-11494797

Fasyani, M. F., Muqsid, A., & Mujtaba, A. W. (2024). Artificial Intelligence and Digital Tafsīr: Assessing the Interpretive Accuracy of ChatGPT’s Engagement with Tafsīr al-Qurṭūbī. Journal of Ushuluddin and Islamic Thought, 2(1), 86–118. https://doi.org/10.15642/juit.2024.2.1.86-118 DOI: https://doi.org/10.15642/juit.2024.2.1.86-118

Forum, W. E. (2025). Putting nature and people at the centre of AI tools. Retrieved from https://www.weforum.org/stories/2025/10/ai-companies-protect-restore-nature/

Gaanoun, K., & Alsuhaibani, M. (2025). Sentiment preservation in Quran translation with artificial intelligence approach: study in reputable English translation of the Quran. Humanities and Social Sciences Communications, 12(1), 222. https://doi.org/10.1057/s41599-024-04181-0 DOI: https://doi.org/10.1057/s41599-024-04181-0

Ghozali, M., & Nadia, M. A. (2023). Exploring Textuality and Reader Orientation: Unveiling Interpretative Tendencies in Understanding Nafs Wahidah in QS. Al-Nisa of the Qur’an. TAFSE: Journal of Qur’anic Studies, 8(2), 191. https://doi.org/10.22373/tafse.v8i2.20339 DOI: https://doi.org/10.22373/tafse.v8i2.20339

Glickman, M., & Sharot, T. (2024). How human–AI feedback loops alter human perceptual, emotional and social judgements. Nature Human Behaviour, 9(2), 345–359. https://doi.org/10.1038/s41562-024-02077-2 DOI: https://doi.org/10.1038/s41562-024-02077-2

Goy, A., Colla, D., Magro, D., Accornero, C., Loreto, F., & Radicioni, D. P. (2020). Building Semantic Metadata for Historical Archives through an Ontology-driven User Interface. Journal on Computing and Cultural Heritage, 13(3), 1–36. https://doi.org/10.1145/3402440 DOI: https://doi.org/10.1145/3402440

Graves, M. (2022). Computational Topic Models for Theological Investigations. Theology and Science, 20(1), 69–84. https://doi.org/10.1080/14746700.2021.2012922 DOI: https://doi.org/10.1080/14746700.2021.2012922

Hakim, M. F., & Nurrohim, A. (2025). Interpretation of The Process of Artificial Intelligence-based Human Creation: Between Chat GPT and Meta AI. Proceeding ISETH (International Summit on Science, Technology, and Humanity), 877–886. https://doi.org/10.23917/iseth.5474 DOI: https://doi.org/10.23917/iseth.5474

Harrag, F., Mahdadi, C., & Ziad, A. N. (2023). Detecting and Measuring Social Bias of Arabic Generative Models in the Context of Search and Recommendation. Advances in Bias and Fairness in Information Retrieval, 155–168. https://doi.org/10.1007/978-3-031-37249-0_13 DOI: https://doi.org/10.1007/978-3-031-37249-0_13

Helm, P., Bella, G., Koch, G., & Giunchiglia, F. (2024). Diversity and language technology: how language modeling bias causes epistemic injustice. Ethics and Information Technology, 26(1), 8. https://doi.org/10.1007/s10676-023-09742-6 DOI: https://doi.org/10.1007/s10676-023-09742-6

Huang, Z., Long, Y., Peng, K., & Tong, S. (2025). An Embedding-Based Semantic Analysis Approach: A Preliminary Study on Redundancy Detection in Psychological Concepts Operationalized by Scales. Journal of Intelligence, 13(1), 11. https://doi.org/10.3390/jintelligence13010011 DOI: https://doi.org/10.3390/jintelligence13010011

Ichwan, M. N., Ming, D., & Sya’roni, M. (2025). Bridging Tradition and Modernity: Integrating Classical Interpretation and Modern Hermeneutics through Ijtihad in Qur’an Studies. Pharos Journal of Theology, 106(2), 1–12. https://doi.org/10.46222/pharosjot.106.2021 DOI: https://doi.org/10.46222/pharosjot.106.2021

Ingram, K. (2021). Constructing AI: Examining how AI is shaped by data, models and people. The International Review of Information Ethics, 29, 1–9. https://doi.org/10.29173/irie415 DOI: https://doi.org/10.29173/irie415

Keskes, I., Zitoune, F. B., & Belguith, L. H. (2014). Learning explicit and implicit Arabic discourse relations. Journal of King Saud University - Computer and Information Sciences, 26(4), 398–416. https://doi.org/10.1016/j.jksuci.2014.06.001 DOI: https://doi.org/10.1016/j.jksuci.2014.06.001

Lenkova, T. A. (2022). Hermeneutics as a basis for the analysis of creolized media text. Litera, (7), 60–69. https://doi.org/10.25136/2409-8698.2022.7.38371 DOI: https://doi.org/10.25136/2409-8698.2022.7.38371

Lindstedt, I. (2024). Muḥammad and His Followers in Context: The Religious Map of Late Antique Arabia. Leiden: Brill. https://doi.org/10.1163/9789004687134 DOI: https://doi.org/10.1163/9789004687134

Mahner, F. P., Muttenthaler, L., Güçlü, U., & Hebart, M. N. (2025). Dimensions underlying the representational alignment of deep neural networks with humans. Nature Machine Intelligence, 7(6), 848–859. https://doi.org/10.1038/s42256-025-01041-7 DOI: https://doi.org/10.1038/s42256-025-01041-7

Manning, C. D., Clark, K., Hewitt, J., Khandelwal, U., & Levy, O. (2020). Emergent linguistic structure in artificial neural networks trained by self-supervision. Proceedings of the National Academy of Sciences, 117(48), 30046–30054. https://doi.org/10.1073/pnas.1907367117 DOI: https://doi.org/10.1073/pnas.1907367117

Mauluddin, M. (2024). Kontribusi Artificial Intelligence (AI) pada Studi Al Quran di Era Digital: Peluang dan Tantangan [The Contribution of Artificial Intelligence (AI) to Quranic Studies in the Digital Age: Opportunities and Challenges]. Madinah: Jurnal Studi Islam, 11(1), 99–113. https://doi.org/10.58518/madinah.v11i1.2518 DOI: https://doi.org/10.58518/madinah.v11i1.2518

Mediamer, G., & Adiwijaya. (2024). Semantic Feature Analysis for Multi-Label Text Classification on Topics of the Al-Quran Verses. Journal of Information Processing Systems, 20(1), 1–12. https://doi.org/10.3745/jips.02.0209

Messeri, L., & Crockett, M. J. (2024). Artificial intelligence and illusions of understanding in scientific research. Nature, 627(8002), 49–58. https://doi.org/10.1038/s41586-024-07146-0 DOI: https://doi.org/10.1038/s41586-024-07146-0

Nishant, R., Schneckenberg, D., & Ravishankar, M. (2024). The formal rationality of artificial intelligence-based algorithms and the problem of bias. Journal of Information Technology, 39(1), 19–40. https://doi.org/10.1177/02683962231176842 DOI: https://doi.org/10.1177/02683962231176842

Nizov, V. (2025). The Artificial Intelligence Influence on Structure of Power: Long-Term Transformation. Legal Issues in the Digital Age, 6(2), 183–212. https://doi.org/10.17323/2713-2749.2025.2.183.212 DOI: https://doi.org/10.17323/2713-2749.2025.2.183.212

OECD. (2021). AI and the Future of Skills, Volume 1: Capabilities and Assessments. Paris. Retrieved from https://www.oecd.org/en/publications/ai-and-the-future-of-skills-volume-1_5ee71f34-en.html DOI: https://doi.org/10.1787/5ee71f34-en

Ortmann, J. (2025). Of opaque oracles: epistemic dependence on AI in science poses no novel problems for social epistemology. Synthese, 205(2), 80. https://doi.org/10.1007/s11229-025-04930-x DOI: https://doi.org/10.1007/s11229-025-04930-x

Ramadhani, R., Nasution, I. F. A., Faza, A. M., Armainingsih, A., & Harahap, A. P. (2025). Semantic Analysis of the Synonymity of the Meaning of Khatama and Ṭaba’a in the Quran: Contextual Relevance for Contemporary Interpretation Studies. Al Qalam: Jurnal Ilmiah Keagamaan Dan Kemasyarakatan, 19(3), 1618. https://doi.org/10.35931/aq.v19i3.4482 DOI: https://doi.org/10.35931/aq.v19i3.4482

Ranaldi, L., & Pucci, G. (2023). Knowing Knowledge: Epistemological Study of Knowledge in Transformers. Applied Sciences, 13(2), 677. https://doi.org/10.3390/app13020677 DOI: https://doi.org/10.3390/app13020677

Rois, C., Muchlis, M., Irfan, A., Anam, H., & Rusdi, R. (2025). ISLAMIC HIERARCHY OF VALUE: Abdullah Saeed’s progressive interpretation of the Qur’an. MIQOT: Jurnal Ilmu-Ilmu Keislaman, 49(1), 205. https://doi.org/10.30821/miqot.v49i1.1125 DOI: https://doi.org/10.30821/miqot.v49i1.1125

Rostam, N. A. P., & Malim, N. H. A. H. (2021). Text categorisation in Quran and Hadith: Overcoming the interrelation challenges using machine learning and term weighting. Journal of King Saud University - Computer and Information Sciences, 33(6), 658–667. https://doi.org/10.1016/j.jksuci.2019.03.007 DOI: https://doi.org/10.1016/j.jksuci.2019.03.007

Saeed, A., & Akbar, A. (2021). Contextualist Approaches and the Interpretation of the Qur’ān. Religions, 12(7), 527. https://doi.org/10.3390/rel12070527 DOI: https://doi.org/10.3390/rel12070527

Salem, A. S. M. (2025). Artificial Intelligence and Human Translation of Selected Qur’anic Verses (Āyāt): A Contrastive Study of Semantic and Interpretative Accuracy. Electronic Journal of University of Aden for Humanity and Social Sciences, 6(3), 369–379. https://doi.org/10.47372/ejua-hs.2025.3.467 DOI: https://doi.org/10.47372/ejua-hs.2025.3.467

Sholihah, F. A., & Mustakim, A. (2025). The Dynamics of Rasm Uthmani and Rasm Imla’i in the Qur’anic Mushaf: A Historical and Practical Study in Indonesia. Al Furqan: Jurnal Ilmu Al Quran Dan Tafsīr, 8(1), 223–238. https://doi.org/10.58518/alfurqon.v8i1.3460 DOI: https://doi.org/10.58518/alfurqon.v8i1.3460

UNESCO. (2025). AI and Education: Guidance for Policy-Makers. Paris. Retrieved from https://www.unesco.org/en/articles/ai-and-education-guidance-policy-makers

van Rooij, I., Guest, O., Adolfi, F., de Haan, R., Kolokolova, A., & Rich, P. (2024). Reclaiming AI as a Theoretical Tool for Cognitive Science. Computational Brain & Behavior, 7(4), 616–636. https://doi.org/10.1007/s42113-024-00217-5 DOI: https://doi.org/10.1007/s42113-024-00217-5

Wazin, W., Siti Patimah, Aan Ansori, & Wasehudin. (2025). Optimizing AI Technology in Assessing Islamic Financing Risks: A SWOT Analysis of Challenges and Opportunities from an Islamic Legal Perspective (Fiqh). Al-Istinbath: Jurnal Hukum Islam, 10(1), 172–193. https://doi.org/10.29240/jhi.v10i1.11941 DOI: https://doi.org/10.29240/jhi.v10i1.11941

Wilkin, C. L. (2022). Developing critical reflection: An integrated approach. The British Accounting Review, 54(3), 101043. https://doi.org/10.1016/j.bar.2021.101043 DOI: https://doi.org/10.1016/j.bar.2021.101043

Yen, D. C., & Davis, W. S. (2019). Knowledge representation. In The Information System Consultant’s Handbook (pp. 535–544). CRC Press. https://doi.org/10.1201/9781420049107-67 DOI: https://doi.org/10.1201/9781420049107-67

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Published

2026-03-27

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Vol. 2 No. 1 (2026): The Future of Quranic Studies in the Era of Artificial Intelligence

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Copyright (c) 2026 Yazdan Kabir, Klapdor Hammond, Ernest Drennen, Sarah Jemali, Rekha Dastyari

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Kabir, Y., Hammond, K., Drennen, E., Jemali, S., & Dastyari, R. (2026). Integration of Artificial Intelligence in the Science of Tafsīr: A Critical Analysis of Opportunities and Challenges for Contemporary Quranic Studies. Al-Qarawiyyin: Jurnal Ilmu Ushuluddin, 2(1), 59-76. https://doi.org/10.64691/3zsxrs39