A primer on artificial intelligence for palliative care educators.

Abstract

Artificial intelligence (AI) is rapidly being adopted in education in the health care professions, including in palliative care. Yet existing AI primers for health professions education (HPE) are not specific to palliative care (PC) and overlook the relational, prognostic, and cultural sensitivities central to the field. This narrative primer addresses that gap. Informed by a review of the literature, it equips PC educators with practical guidance for responsibly harnessing AI. We first introduce foundational AI concepts relevant to educators and clinicians, including machine learning (ML), large language models (LLMs), generative AI (GenAI) and agentic AI. We then trace a progression from general HPE use, such as study support, assessment, and AI-enhanced simulation, to PC-specific applications in curriculum design, serious-illness communication training, and interprofessional teamwork. Throughout, we situate the risks where they arise, with attention to concerns most consequential for PC: bias, communication integrity and hallucination, data privacy, and over-reliance on AI, in a field where relational, humanistic practice and nuanced communication are central. Guiding principles of ethics, equity, and patient-centeredness anchor the discussion. We close with concrete implications for educators and curriculum development: building AI literacy, establishing governance and appropriate-use policies, and verifying AI-generated outputs against trusted sources. The aim is an educator-AI partnership that safeguards what is essential in PC: compassionate, dignified, patient-centered decision-making and care.