The use of artificial intelligence in medicine is expanding rapidly. Much of this expansion has come from the development of a branch of artificial intelligence called Generative Artificial Intelligence, which brings together a set of mathematical and statistical techniques that allow processing vast amounts of information to generate new content. Among the most promising examples of this technology are Large Language Models (LLMs). Tools such as ChatGPT and Claude showcase how these types of generative AI can produce human-like text, answer complex questions, and even create original content. This novel class of AI also opens the door to transformative applications in clinical decision-making and patient-physician interactions. With the ability to process vast amounts of data and generate new insights, LLMs have the potential to not only assist clinicians in diagnosing and treating patients more efficiently but also to redefine the entire clinical workflow. As these tools become more integrated into health care, the very nature of the clinician’s role could shift from a traditional model of knowledge gatekeeping to a more dynamic partnership with AI, where the focus can increasingly turn toward patient-centered care, empathy, and personalized treatment. This radical shift in clinical practice could ultimately reshape how physicians and patients interact, with AI playing a central role in guiding and informing medical decisions. In the following, we will provide an overview of some trends and uses of LLMs in medicine and discuss some normative implications arising from the increasing proliferation of LLMs in medicine.