Intelligent traditional Chinese medicine (TCM) is a key pathway toward the modernization and globalization of TCM in the era of artificial intelligence. Due to its unique terminology and diagnostic framework, TCM's intelligentization process has long faced a range of challenges, from the digitization and formalization of knowledge bases to the differentiation of syndromes and personalized treatment. Recently, the advent of large language models (LLMs) like GPTs has marked a transformative milestone in semantic understanding tasks, attracting widespread attention from the medical, academic, and industrial communities. Nonetheless, LLMs often suffer from accuracy and logical reasoning limitations within specific fields and may manifest hallucinations in the generative outputs. Through a comprehensive review of existing literature and empirical analyses, this study delves into the potential and challenges of adapting LLMs to TCM. Promising perspectives on future developments at this innovative intersection are discussed.