Studies of the Islamic Revolution, as an interdisciplinary field, face challenges such as the vast volume of historical sources, the multiplicity of ideological narratives, and the semantic complexities of data. In recent years, the entry of artificial intelligence (AI) into the humanities has provided new capacities for analyzing these data, while simultaneously turning its methodological position in historical research into a contentious issue. This article, through an analytical-critical approach, addresses the question of whether artificial intelligence in studies of the Islamic Revolution is merely a tool for facilitating and accelerating existing research processes, or whether it can function as an emerging methodology with its own distinct epistemological logic. The research method is based on conceptual analysis and the presentation of a "demonstrative case study," in which the logic of applying some common computational methods of historical text analysis is reconstructed and interpretively evaluated on a limited but real corpus of texts related to the transformation of the discourse of the "oppressed." The findings indicate that at the instrumental level, artificial intelligence is capable in managing big data and identifying macro-discursive patterns; however, at the methodological level, sole reliance on it can lead to the reduction of meaning, algorithmic bias, and the reproduction of hegemonic readings. In conclusion, the article, by proposing the concept of "responsible digital hermeneutics," emphasizes the necessity of a hybrid human-algorithm model in which the final interpretation remains the responsibility of the human historian.