Exploring the Ethical Dimensions of AI ‐Driven Patient Monitoring in Critical Care Nursing: A Systematic Review

BACKGROUND: Artificial intelligence (AI) is increasingly applied in intensive care units (ICUs) to enhance monitoring, prediction and decision-making. While these systems may improve patient safety and support nursing practice, their integration raises significant ethical concerns. AIM: To explore the ethical dimensions of AI-driven patient monitoring in critical care nursing, focusing on autonomy, privacy, accountability and equity as reported by ICU nurses and patients. STUDY DESIGN: A systematic search of PubMed, CINAHL, PsycINFO, Scopus and ProQuest Central identified empirical studies published between 2010 and 2025 that addressed ethical implications of AI in ICU nursing. RESULTS: Six studies were included: three cross-sectional surveys, two qualitative interview studies and one pilot feasibility trial, involving 837 ICU nurses and 22 ICU patients. Four ethical themes were identified. Autonomy: Nurses feared automation bias and erosion of judgement, though trust in AI reduced decision regret. Privacy: Continuous data collection raised strong concerns, with governance and training seen as prerequisites for adoption. Accountability: Lack of algorithmic transparency limited nurses' willingness to act on outputs. Equity: Risks of biased datasets and subgroup disparities threatened fair care delivery. CONCLUSIONS: AI-driven monitoring can enhance nursing practice but introduces ethical vulnerabilities. Protecting autonomy, safeguarding privacy, ensuring transparency and addressing equity are essential for responsible integration in critical care nursing. RELEVANCE TO CLINICAL PRACTICE: Nurses require enhanced AI literacy and ethical training to integrate technology with patient-centred care. Robust governance must clarify accountability and ensure transparency, while research should focus on long-term impacts and develop nursing-specific ethical frameworks.