NAIL-G: a conceptual best-fit framework for nursing ai literacy and governance anchored in socio-technical safety science

BACKGROUND: Artificial intelligence is reshaping health care delivery and education, but nurses lack discipline-specific guidance that integrates artificial intelligence literacy with socio-technical safety and governance. Existing AI literacy and digital competence models are often generic and do not reflect nursing standards, work systems or responsibilities for patient safety and equity. METHODS: A best-fit framework synthesis and concept development were used to integrate scholarship on artificial intelligence literacy, digital competence, socio-technical safety, nursing competency standards and policy guidance on transparent use of artificial intelligence in scholarly work, with extracted constructs mapped to the AACN Essentials and socio-technical work-system dimensions. RESULTS: The Nursing Artificial Intelligence Literacy and Governance (NAIL-G) framework comprises five domains covering Foundations & Tools; Quality, Safety & Risk; Professionalism, Ethics & Law; Systems, Equity & Social Impact; and Scholarship, Communication & Governance. It positions artificial intelligence literacy as competency-plus-governance, emphasizing critical judgement, verification, disclosure and equity-aware practice across nursing education, clinical work and scholarly communication. CONCLUSIONS: NAIL-G offers curriculum designers, educators, regulators and clinical leaders a structured way to embed artificial intelligence capabilities, safeguards and governance expectations across nursing practice and education. The framework can guide integration of artificial intelligence-related learning outcomes, assessment tasks and safety checks into curricula, support reflective use of artificial intelligence in clinical reasoning and documentation, and strengthen nurses’ confidence to raise concerns about unsafe or inequitable systems.