Sialendoscopy has emerged in the last decades as a groundbreaking technique, offering a minimally invasive approach for exploring and managing salivary gland disorders. More recently, the advent of chatbots, powered by advanced natural processing language and artificial intelligence algorithms, has revolutionized the way healthcare professionals and patients access and analyze medical information and potentially will support soon the clinical decision-making process.

A prospective, cross-sectional study was designed to assess the level of agreement between Chat-GPT and 10 expert sialendoscopists aiming the capabilities of Chat-GPT to further improve the management of salivary gland disorders.

The mean level of agreement was 3.4 (SD: 0.69; Min: 2, Max: 4) for Chat-GPT's answers while it was 4.1 (SD: 0.56; Min: 3, Max: 5) for the group of EESS (p < 0.015). The overall Wilcoxon signed-rank test yielded a significance level of p < 0.026 when comparing the level of agreement between Chat-GPT and EESS. The mean number of therapeutic alternatives suggested by Chat-GPT was 3.33 (SD: 1.2; Min: 2, Max: 5), while it was 2.6 (SD: 0.51; Min: 2, Max: 3) for the group of EESS; p = 0.286 (95% CI − 0.385 to 1.320).

Chat-GPT represents a promising tool in the clinical decision-making process within the salivary gland clinic, particularly for patients who are candidates for sialendoscopy treatment. Additionally, it serves as a valuable source of information for patients. However, further development is necessary to enhance the reliability of these tools and ensure their safety and optimal use in the clinical setting.