Transforming the Humanities: Artificial Intelligence and Digital Learning in Literary Studies

Abstract

The integration of Artificial Intelligence (AI) and digital learning technologies into the domain of literary studies represents a profound and multifaceted transformation in how literature is taught, read, interpreted, and researched. Traditionally grounded in close reading, textual criticism, and hermeneutics, literary studies has historically resisted quantification. However, the emergence of Natural Language Processing (NLP), machine learning algorithms, digital humanities platforms, and AI-assisted pedagogical tools has opened entirely new avenues for scholarly engagement with texts. This paper investigates the convergence of AI and digital learning within literary education, examining how computational approaches such as sentiment analysis, stylometric profiling, topic modelling, and AI-driven tutoring systems are reshaping the intellectual landscape of literature classrooms and research environments. Drawing upon a qualitative-analytical framework, the study explores the theoretical implications, pedagogical applications, and ethical concerns surrounding AI adoption in literary academia. The paper further identifies existing research gaps in non-Western and multilingual literary contexts and proposes future directions for inclusive, culturally responsive AI integration. Ultimately, this study argues that AI, when critically deployed, can enrich literary interpretation rather than diminish it, fostering a new generation of digitally literate humanists equipped for contemporary academic challenges.