Cultural heritage requires protection for preservation. Artificial Intelligence technologies present innovative methods to extract valuable insights from digital literature and understand complex themes in literary data. This study applies artificial intelligence methods to cultural heritage literature in order to detect overtourism impacts on the preservation of cultural artifacts and historical sites. Six different topic modeling techniques-Latent Dirichlet Allocation, Latent Semantic Indexing, Hierarchical Dirichlet Process, Non-Negative Matrix Factorization, Structural Topic Modeling, and Correlated Topic Modeling-have been used to determine topics. The analysis reveals that overtourism is a multifaceted issue that significantly impacts cultural heritage. Many topics overlap across different models, such as overtourism and its impact, and cultural heritage and identity.