Metabolic metaphors in cognition: Assimilating information in the artificial intelligence era

The rapid growth of biomedical literature and the widespread availability of artificial intelligence (AI) have changed how medical knowledge is accessed, learned, and applied. Although these developments make information retrieval faster and easier, access to information does not necessarily lead to deeper understanding or better clinical reasoning. This article introduces the concept of 'knowledge obesity' to describe a situation in which the accumulation of information exceeds an individual's capacity to critically evaluate, integrate, and apply it. Using a metabolic analogy, the article frames learning as a process in which information must be selected, processed, and incorporated into existing knowledge to support clinical judgment. Personal experiences from the pre-digital era are used to illustrate how the effort involved in finding scientific literature once shaped the learning process and how this experience differs from today's immediate access to information. The article also discusses cognitive offloading and the potential consequences of overreliance on AI, while recognising its value in filtering information and reducing time spent on routine tasks. The concept of 'Cognitive Ozempic' is proposed as a metaphor for selectively using AI to manage information overload and redirect human effort toward critical thinking, scientific inquiry, and clinical decision-making. Rather than replacing the intellectual work required for learning, AI should support a more deliberate and reflective approach to medical education.