Generative artificial intelligence in otolaryngology

The objective of this narrative review is to provide a general knowledge base regarding generative artificial intelligence (AI) within otolaryngology for clinicians and researchers in the field. AI is quickly becoming pervasive throughout society and finding novel applications in healthcare. As such, it is increasingly important for healthcare providers to become well versed in the topic. This article begins with a breakdown of how large language models (LLMs), the backbone of generative AI, function. The authors then present an overview of how LLMs have been applied to otolaryngology education and clinical workflow, highlighting the importance of Retrieval-Augmented Generation in building evidence-based clinical tools and references. Next, the article presents a thorough review of available research on the use of LLMs to provide patient education in otolaryngology. Articles were identified by querying PubMed, Embase, and Cochrane Library from 2023 to July 2025. Research suggests that LLMs can generate comprehensive patient education content at an appropriate reading level and provide a fair level of accuracy in response to patient questions on most otolaryngology topics. However, accuracy varies immensely depending on the specific LLM used, the format of the question or prompt, and the type of response elicited. Finally, the authors provide a brief look into the legal developments pertaining to AI use in healthcare, a critical angle to remain cognizant of as this technology gains wider presence in clinical practice.