Explicitation in Artificial Intelligence–Driven Machine Translation: A Comparative Analytical Study of Classical Arabic Heritage Texts and Their English Renditions

This study investigates the phenomenon of explicitation in artificial intelligence-driven machine translation, with particular focus on the transfer of implicit meanings from Classical Arabic heritage texts into English.The research addresses a central question concerning the extent to which contemporary AI-based translation systems are capable of identifying, interpreting, and making explicit culturally, linguistically, and contextually embedded meanings that are characteristic of classical Arabic discourse.Adopting a qualitative comparative analytical approach, the study examines a carefully selected corpus of classical and religious heritage texts.Machinegenerated English translations are analyzed to identify different types and levels of explicitation, including obligatory structural explicitation and optional pragmatic or stylistic expansion.The analysis evaluates the degree to which these explicitation strategies align with English linguistic norms, communicative clarity, and target audience expectations, while also assessing the risk of over-translation or semantic distortion.The findings indicate that AI-powered translation systems demonstrate a growing capacity to enhance semantic transparency through the clarification of elliptical structures, the specification of implicit references, and the restructuring of complex rhetorical patterns typical of Classical Arabic.At the same time, the results reveal limitations related to contextual sensitivity, cultural nuance, and stylistic appropriateness, particularly in texts containing religious, historical, or culturally loaded expressions.The study concludes that while artificial intelligence has achieved significant progress in handling explicitation as a linguistic and communicative strategy, its performance remains uneven in domains requiring deep pragmatic interpretation and cultural competence.The research contributes to ongoing discussions on the role of AI in scholarly translation and highlights its potential as a supportive tool for academic, heritage, and research-oriented applications, rather than a full substitute for expert human translation.