We are surrounded by narratives, and in today’s world, there is a growing need for a deeper understanding of how generative artificial intelligence technology perceives and interacts with narratives and storytelling. The aim of this study is to identify the boundaries of knowledge, recognize, and classify scientific achievements in this interdisciplinary field. Accordingly, by systematically identifying, reviewing, and analyzing over 1,000 academic works in this domain, the study addresses which aspects and approaches of narratology researchers have focused on in relation to artificial intelligence. It also maps the main areas of study and research topics based on the theories of Gérard Genette and Seymour Chatman within the framework of narrative theory. The findings reveal that, up to the time of this study, the greatest attention has been given to components such as story, discourse, time, character, event, and audience, while studies related to dialogue and narrative action have been secondary priorities. This appears to be influenced by the characteristics of narrative creation and analysis through a non-human agent, which has yet to fully grasp the complexities of narrative construction. Consequently, researchers’ focus and research topics have centered on how artificial intelligence understands and creates fundamental narrative structures. The study demonstrates that despite significant global advances in natural language processing and computational narratology, many research areas remain unexplored, and addressing these can provide a more comprehensive picture of the intersection between the broad fields of narrative and artificial intelligence.