Artificial intelligence leadership in nursing management for Nursing Organisations: A Concept Analysis

Background: Artificial intelligence (AI) is increasingly embedded in nursing management through workforce modelling, quality surveillance, resource allocation and organisational decision support. However, artificial intelligence leadership in nursing management remains conceptually underdeveloped, particularly regarding governance, accountability and nursing-specific leadership responsibilities. Objective: To analyse and define artificial intelligence leadership in nursing management and develop a conceptual framework for future empirical research, competency development and responsible AI implementation. Design: A concept analysis using Walker and Avant’s eight-step methodology, supported by a structured search to identify conceptually relevant interdisciplinary literature. Setting: Peer-reviewed interdisciplinary literature and authoritative policy and professional guidance documents identified through PubMed, Google Scholar, Europe PMC, ProQuest Nursing & Allied Health Database and relevant authoritative sources, published between 2020 and 2025. Main outcome measures: Defining attributes, antecedents, consequences, model cases and empirical referents. Results: Twenty-four substantive sources were retained for conceptual analysis; methodological and theoretical foundations were used separately to guide analysis and support theoretical positioning. Artificial intelligence leadership in nursing management was conceptualised as a governance-specialised extension of nursing leadership comprising five interrelated attributes: strategic AI direction-setting, managerial AI literacy, ethical and regulatory oversight, organisational change leadership and workforce capability development, and systematic integration into nursing management processes. Antecedents were organised as core or contextual conditions; consequences were differentiated into proximal and proposed distal consequences, the latter requiring empirical validation. Empirical referents were identified at individual, workforce and organisational levels. Conclusions: Artificial intelligence leadership in nursing management clarifies the leadership responsibilities required when AI informs nursing managerial decision-making, including algorithmic accountability, human oversight and preservation of professional nursing judgement. The concept provides a foundation for competency development, empirical validation and organisational governance across health and aged care settings, including Asia-Pacific contexts.