Artificial Intelligence in Nursing Governance and Regulation: An Umbrella Review of Ethical and Policy Dimensions.

BACKGROUND: As AI becomes increasingly embedded in healthcare systems, nursing governance faces new challenges involving ethical accountability, professional autonomy, data stewardship, and institutional oversight. Existing reviews highlight fragmented understanding of how these changes impact the nursing profession. AIM: This umbrella review aimed to synthesize ethical and policy dimensions related to the integration of artificial intelligence (AI) within nursing governance and regulatory frameworks. METHODS: Following JBI guidance and PRISMA 2020, five databases were searched for reviews published from January 2010 to December 2025. Reviews were appraised and synthesized by purpose, quality, nursing specificity, and primary study overlap, which was quantified using a citation matrix and Corrected Covered Area (CCA). FINDINGS: Thirty-one reviews included 23 evidence syntheses and eight evidence maps. Privacy or data stewardship appeared in 29 reviews, transparency or explainability in 27, bias or fairness in 25, accountability or liability in 25, consent or autonomy in 18, leadership, education, or oversight in 14, and safety or human oversight in nine. Among 23 reviews with enumerable, extractable study lists, the CCA was 0.54%, indicating slight overlap. Nursing-specific concerns involved professional judgment, representation, oversight, regulatory variation, and ethical preparedness. CONCLUSION: AI creates linked governance concerns involving data, fairness, transparency, autonomy, and accountability. Auditable responsibilities are needed across clinical, institutional, and regulatory levels while preserving nursing judgment and patient advocacy. Evidence for specific regulatory models remains limited.