Muhammad Rapi
This chapter reviews how artificial intelligence (AI) has transformed literary interpretation, promoting cross-cultural understanding and multidisciplinary methods. Researchers may analyze large literary collections, uncover patterns, and study national emotional and thematic frameworks using AI technologies like natural language processing, sentiment analysis, and machine learning. AI-driven analysis enhances and recontextualizes literary ideas including formalism, structuralism, post-structuralism, and reader-response. Global literature, folklore, translation, and genre evolution case studies show AI's ability to find universal themes and cultural differences. Authorship, bias, and data equity are addressed in the chapter to promote inclusive and responsible AI use in literary studies. This multimodal approach makes AI a powerful tool for understanding literary human expression and cultural narratives. © 2026, IGI Global Scientific Publishing. All rights reserved.
Universitas Negeri Makassar, Indonesia
