Nursing, omics, and artificial intelligence: Precision health's trifecta

Precision health individualizes care by integrating biological, environmental, and social drivers of health, a perspective that aligns with the holistic lens of nursing. Advances in omics, including genomics, epigenomics, transcriptomics, proteomics, microbiomics, and metabolomics, have expanded our understanding of health and disease. However, the complexity of these data has often limited integration into clinical practice. Artificial intelligence (AI) is rapidly transforming precision health in nursing by making omics complexity actionable. This paper argues that nursing must actively engage in shaping the integration of AI and omics across the three pillars of the profession: education, research, and practice. In education, AI-powered tools can support adaptive learning, simulation, and curriculum development to strengthen nurses' literacy in omics and data-driven health care. In research, machine learning and generative AI tools can enhance the analysis of high-dimensional omics datasets, streamline study development, and accelerate translation of research findings into precision health interventions. In clinical practice, AI-assisted documentation and administrative support, pharmacogenomic tools, and remote patient monitoring systems inform individualized, complex care plans and improve clinical efficiency and nurse satisfaction. Realizing this potential, however, requires careful attention to ethical, legal, and social considerations, including transparency, bias, privacy, and human oversight. Nurses, consistently recognized as the most trusted health professionals, are uniquely positioned to ensure that the integration of AI and omics remains equitable, ethical, and patient-centered, ultimately advancing precision health and improving patient outcomes.