Humanistic Meaning-Making and Behavioral Governance in AI-Mediated Nursing Care

AI has supported nursing and health care for years through decision support, prediction, monitoring, and workflow tools; what is changing is the breadth and proximity of AI-generated information to everyday care. Existing nursing AI literature has advanced AI literacy, safety, ethics, and governance, yet less attention has focused on how AI-mediated care reshapes contextual nursing judgment, patient recognition, professional behavior, and relational accountability at the point of care. Nursing digital competence may therefore increasingly need to extend beyond AI literacy toward humanistic meaning-making and behavioral governance. We offer MESH as a provisional integrative nursing lens with 4 domains: meaning-making, ethical presence, system and relational workflow governance, and human-in-the-relationship. Standardized nursing data are considered one enabling bridge through which nursing-sensitive information may remain visible within AI-supported decision environments. The MESH-action cycle—recognize, interpret, communicate, govern, and evaluate—is proposed as a 5-step practice-oriented pathway for applying these domains. MESH is not a validated competency model; its purpose is to support inquiry, education, implementation design, and empirical testing of whether AI augments or obscures nursing judgment and patient recognition.