DATAFYING REVELATION: AI-ASSISTED INTERPRETATION OF THE QUR’AN AND HADITH
Abstract
The rapid expansion of artificial intelligence in digital humanities has begun to reshape scriptural studies, including the interpretation of the Qur’an and Hadith. The transformation of sacred texts into machine-readable data structures introduces both analytical opportunities and epistemological challenges, particularly concerning interpretive authority and theological coherence. This study aims to examine the feasibility, reliability, and epistemic implications of AI-assisted interpretation within an Islamic hermeneutical framework. A mixed-methods design was employed, integrating computational text analysis, semantic clustering, and isn?d network modeling with expert-based hermeneutical evaluation grounded in classical u??l al-fiqh and ?ul?m al-hadith principles. The dataset included selected Qur’anic verses and authenticated Hadith narrations representing legal, theological, and narrative domains. Findings indicate high linguistic accuracy (above 93%) and strong thematic alignment with classical exegesis in jurisprudential texts, while performance decreased in metaphor-rich theological passages. Statistical analysis confirmed significant convergence in structured legal contexts (p < 0.001). The study concludes that AI-assisted interpretation is most effective as an augmented hermeneutical tool operating under scholarly supervision rather than as an autonomous interpretive authority. Responsible integration of computational models can enhance analytical efficiency while preserving normative theological boundaries.
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References
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Copyright (c) 2026 Ahmad Zainal Abidin, Erwin Notanubun, Zeynep Toprak, Daniel Schmidt
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