Principals’ ethical leadership in the AI Era: A narrative literature review of emerging challenges, strategies, and outcomes

The integration of artificial intelligence (AI) into education has intensified questions about how principals exercise ethical leadership in the adoption and governance of emerging technologies. This article reports a systematic review of research published between 2018 and July 2025 at the intersection of school leadership, ethics, and AI. Using a PRISMA-informed search databases, 62 peer-reviewed studies were identified and synthesized. The analysis revealed four categories of insight: trends in principals' experiences of dilemmas such as balancing efficiency with equity, strategies for acting in contexts where guidance is limited, influencing factors including policy frameworks and school cultures, and outcomes ranging from increased trust to organizational conflict. From these findings, the Principals' Ethical AI Leadership (PEAIL) framework was developed. The framework conceptualizes leadership not as a linear progression of phases, but as a prism refracting simultaneous demands at individual, organizational, and systemic levels. Despite this emergent body of work, three important gaps remain. First, theoretical approaches are not well integrated across normative, critical, and sociotechnical traditions. Second, leadership preparation and professional learning rarely address AI ethics explicitly. Third, there is little empirical evidence linking principals' ethical choices about AI to classroom practices or to students’ learning and well-being. Future directions include embedding AI ethics into leadership training, designing empirical studies that trace leadership decisions to student outcomes, and developing policies that institutionalize accountability and equity. By identifying these gaps and outlining concrete pathways forward, the article provides both a conceptual framework and a practice-oriented agenda for ethical school leadership in the AI era. • Synthesizes 62 K–12 studies (2018–2025) on principals' ethical leadership and AI using PRISMA. • Identifies multi-level ethical tensions: privacy, bias, opacity, vendor dependence, and autonomy. • Introduces PEAIL: ethical leadership as socio-technical stewardship in AI-mediated schools. • Maps actionable strategies: human oversight, data protection, capacity building, equity, and policy alignment. • Outlines a research/practice agenda linking leadership decisions to classroom and student outcomes.