Hadith literacy in the digital era is an urgent need to address the epistemological and cultural challenges faced by Generation Z, who tend to access religious knowledge through digital media without an adequate scientific literacy framework. The phenomenon of technological disruption has prompted the need to reconstruct the approach to hadith literacy to bridge classical scientific traditions with contemporary digital realities. This study aims to develop an artificial intelligence (AI)-based digital hadith literacy model that can strengthen Generation Z’s ability to understand, verify, and contextualize hadith critically and systematically. Using a qualitative-descriptive method through a conceptual design based on the integration of hadith studies and AI technology, this study analyzes in depth four main aspects: the conceptual reconstruction of digital hadith literacy, the integration of AI algorithms in mapping sanad and matan (translations of the narrators), the design of a digital hadith literacy model, and a conceptual test of the feasibility and implications of the model. The results of this study indicate that the development of a digital hadith literacy model can present a new paradigm for hadith learning that is interactive, adaptive, and analytical, where AI acts as an epistemological partner in identifying the validity of sanad (chain of transmission), classifying hadith themes, and presenting scientific data visualizations that facilitate the digital literacy process. Conceptual testing proves that this model has theoretical feasibility and high potential in strengthening the understanding of hadith based on data and context, while simultaneously encouraging the transformation of Islamic literacy of Generation Z towards a more critical, integrative, and oriented towards the authenticity of sources. This research has significant implications for the development of contemporary hadith study methodologies and digital Islamic education strategies based on scientific and authentic principles.