The rapid advancement of artificial intelligence (AI) has significantly transformed language education, including

the teaching and learning of Arabic, which plays a pivotal role in accessing Islamic texts such as the Sunnah of

the Prophet. However, mastering the four fundamental language skills (listening, speaking, reading, and writing)

remains a major challenge, particularly among non-native speakers (NNAS) aiming to comprehend classical and

context-rich Hadith texts. This study aims to explore the potential of AI in enhancing Arabic language proficiency

to improve comprehension of Sunnah texts. A qualitative research design was employed, involving content

analysis of selected AI-based tools like automated translation software and natural language processing (NLP)

scaffolding (Constructivist Learning Theory), which enhances the learner's perceived usefulness of the

technology (Technology Acceptance Model, TAM). The study concludes that AI holds promising potential as an

effective, immediate supplementary instructional tool in modern Islamic education, accelerating NNAS access to

The background issue driving this study stems from the critical linguistic barrier faced by non-native Arabic

speakers (NNAS) in comprehending complex Islamic source texts, particularly the Prophetic Sunnah (Hadith).

While Arabic is the primary language for Islamic jurisprudence and guidance, the proficiency gap across the four

core skills (listening, speaking, reading, and writing) among NNAS students significantly impedes a nuanced and

of limited Arabic linguistic proficiency hindering the accurate and contextual understanding of Sunnah texts

among NNAS students.

The general objective of this study is to explore the potential of AI in augmenting NNAS students’ Arabic

language skills for enhanced comprehension of Sunnah texts. Specific objectives include: (1) analysing the

features and effectiveness of AI tools (e.g., alminasa.ai, usul.ai) in improving Arabic vocabulary and grammar

accuracy; and (2) determining how the integration of AI can facilitate a deeper, contextual understanding of

Hadith narratives. The research questions seek to ask: (1) How effectively do current AI applications enhance

NNAS students’ Arabic vocabulary and grammatical accuracy? (2) What are the perceived benefits and

challenges of integrating AI for understanding the contextual nuances of Sunnah texts? The scope and limitations

of this qualitative study focus on the content analysis of specific AI applications. Nonetheless, the contribution

Technology Acceptance Model (TAM). Constructivism, as highlighted by Vygotsky, emphasizes that learners

actively construct knowledge and meaning, suggesting that AI tools can serve as potent Zone of Proximal

Development (ZPD) enhancers, providing adaptive scaffolding for non-native Arabic speakers (NNAS) to master

complex Hadith texts (Mulyanto et al., 2024). TAM is crucial for critically analysing user acceptance both by

students and instructor of AI applications, assessing the perceived ease of use and perceived usefulness in

improving Arabic proficiency (Hassan & Ahmad, 2021). Relevant prior findings consistently demonstrate AI’s

effectiveness in fast-tracking vocabulary acquisition and grammatical accuracy in foreign language learning,

particularly through interactive Natural Language Processing (NLP) and intelligent tutoring systems (Chen &

Chen, 2023). However, the conceptual definitions are crucial: AI is defined functionally as interactive tools (e.g.,

alminasa.ai, usul.ai) facilitating language practice; Arabic language skills refer to the four core competencies;

studies rarely move past basic linguistic skills to address the hermeneutic challenges. The Conceptual Framework

for this study is thus structured based on this gap: it links the input (AI Tools and Features, grounded in TAM) to

the process (Enhanced Arabic Skills, informed by Constructivism), culminating in the desired outcome (Deeper

Understanding of Prophetic Sunnah Texts). This framework allows for a critical analysis of the current limitations

of generic AI models when dealing with the nuanced, high-context linguistic demands of religious heritage texts

(Mohamad & Omar, 2020).

The study employed a qualitative design focused on document analysis to investigate the utility of Artificial

Intelligence (AI) in enhancing Arabic language skills for understanding Sunnah texts. The study population was

comprised of authentic Prophetic Sunnah texts related to dhikr and du'a. The sample consisted of three selected

translation accuracy and semantic integrity.

Based on the document analysis comparing the AI-generated translations with established Islamic texts, the

study's findings describe the potential and accuracy of AI platforms in translating Prophetic Sunnah texts. The

research design was qualitative, focusing on document analysis as the data collection method. Specifically, the

study analysed selected Hadith texts and the translations generated by the AI platform usul.ai. The translations

were then benchmarked against the established translations found in the book Kitab Perisai Muslim.

The comparison revealed a high degree of fidelity in the AI translation of short supplication phrases. For the

phrase "

the AI-generated translations of dhikr and du'a compares favorably with previous findings that validated AI's

effectiveness in enhancing vocabulary and grammatical accuracy in foreign language acquisition (Chen & Chen,

Theoretically, these findings are logically explained through the combined lens of the Constructivist Learning

Theory and the Technology Acceptance Model (TAM). The AI-generated translations, which offer multiple close

interpretation.

The implications of these findings are significant for practice, policy, and theory. Practically, the high accuracy

of AI translations suggests that these platforms can be integrated into Arabic language curricula as effective,

immediate supplementary tools for NNAS students, accelerating access to Islamic sources. For policy, these

results encourage institutional leaders to formulate strategies for the ethical adoption of AI in religious education,

moving beyond skepticism towards leveraging technology for pedagogical enhancement. Theoretically, the study

contributes new evidence to the Constructivist model by validating AI as an effective digital mediator for

hermeneutic learning within specialized religious studies. The novel finding and key contribution of this study is

the empirical demonstration of AI's capability to deliver semantically reliable, near-reference translations of core

Sahih Muslim dhikr and du'a texts, thereby lowering the linguistic barrier to authentic Islamic knowledge for a

global audience.

The main conclusion of this study is that AI platforms demonstrate significant potential and accuracy in

translating Prophetic Sunnah texts, specifically dhikr and du'a from Sahih Muslim. The high fidelity of the AI

translations, which closely align with established reference texts like Kitab Perisai Muslim, empirically