Large Language Models in Alzheimer’s Care: Clinical Use Cases, Safety Challenges, and Implementation Pathways

Background

Alzheimer’s disease (AD) care is increasingly communication-intensive, requiring sustained caregiver education, symptom monitoring, behavioral management, and coordination across fragmented clinical settings. Large language models (LLMs) can generate, summarize, and adapt natural language at scale, creating opportunities to support dementia care workflows, but they also introduce safety risks that may be amplified in cognitively vulnerable populations.