This study explores the potential use of ChatGPT, an AI-based language model, in assessing herbal-drug interactions (HDi) to enhance clinical decision-making. HDi can pose significant health risks by reducing drug efficacy or causing unwanted side effects. Clinical pharmacists play a key role in identifying these HDIs, and currently, there are limited tools available for checking drug interactions. The research focuses on a case study of a rectal adenocarcinoma patient treated with capecitabine and 26 supplements, which contain a total of 80 herbal substances. ChatGPT 3.5 was asked three questions regarding potential HDIs: "Are there possible HDIs?", "What is the pharmacokinetic mechanism?", and "What is the bibliographic source of the interaction?". The results were reviewed by an oncology clinical pharmacist and compared to existing databases and independent bibliographic research. The findings highlight ChatGPT's advantage in processing large amounts of data quickly, with 16% of interactions classified as "unlikely", confirmed by the pharmacist. However, 73% of the suggested mechanisms were false positives, and 4% were categorized as "hallucinations". Additionally, most of the bibliographic sources provided by ChatGPT were outdated or unavailable. While ChatGPT proves useful for initial HDI screening, its limitations include outdated data (last updated in January 2022), lack of access to private databases, and occasional inaccuracies. Further applications of AI in this area are recommended, though expert validation remains essential in the clinical decision-making process.