Generative artificial intelligence

Generative artificial intelligence (GenAI) refers to a class of artificial intelligence systems, typically built on large language models and related generative architectures, that can create new content such as text, images, audio, or video in response to prompts or other inputs. In biomedical and health-related settings, GenAI is increasingly used to draft text, summarize information, generate educational materials, support documentation, and assist with decision-making workflows. Its rapid adoption has been driven by the ability of these systems to produce human-like language and other outputs at scale.

From a medical and scientific perspective, GenAI is significant not because it functions as a biological agent, but because it is becoming embedded in clinical, educational, and administrative processes that affect patient care, learner performance, and professional practice. Recent research has emphasized both its utility and its limitations: outputs may be useful for accelerating tasks such as protocol drafting, note generation, and educational content creation, but they require structured human oversight, validation, and attention to ethical, regulatory, and safety concerns. In contexts such as mental health support, clinical documentation, and medical education, GenAI is being evaluated alongside artificial intelligence more broadly for performance, reliability, and risk.