Alzheimer’s disease and related dementias (ADRD) remains a major health crisis with profound social and economic burdens. Innovative strategies are needed to identify genetic risk and protective factors, model disease mechanisms, and accelerate therapeutic discovery. Advances in trustworthy AI and informatics now enable the integration of multimodal genetics, omics, imaging, and outcome data from large biobanks, creating powerful opportunities for biomarker and gene discovery beyond categorical diagnoses. At the same time, generative AI and large language models (LLMs) extend these capabilities to text-rich sources such as the scientific literature, clinical notes, and caregiver narratives. When integrated with knowledge graphs, LLMs can dynamically retrieve and synthesize domain-specific knowledge.