AI in hematology: A new frontier for nursing practice and patient care.

Artificial intelligence (AI) is reshaping hematology by enabling faster, more accurate diagnostics and risk prediction. However, the success of AI integration depends not only on technological capability but also on the role of nurses-who act as frontline caregivers, interpreters of data, and patient advocates. Hematology nurses are uniquely positioned to bridge the gap between AI tools and patient-centered care, especially in high-stakes scenarios such as leukemia management and stem cell transplantation. To examine the current and potential roles of hematology nurses in implementing AI technologies, identify benefits and challenges of AI in nursing workflows, and propose practical strategies for ethically and effectively integrating AI into hematology nursing practice. We conducted a systematic scoping review guided by the PRISMA-ScR framework. Databases searched included PubMed and relevant grey literature using terms related to "artificial intelligence," "hematology," and "nursing." Studies were mapped across four domains: diagnostics, monitoring and prediction, treatment support, and patient engagement. The socio-technical framework and ethical lens were used to analyze implications for nursing roles, workflows, and patient safety. Regional insights from the Gulf and Saudi Arabia were incorporated. The review identified significant advances in AI applications across hematology nursing domains: • Diagnostics: AI tools like Morphogo improve cell classification accuracy (~99%), enabling earlier leukemia detection. • Prediction: Machine learning models integrated into EHRs predict sepsis or neutropenia before clinical onset, allowing proactive nursing intervention. • Treatment Planning: AI-enabled decision support tools assist in chemotherapy adjustments and workflow optimization, with nurses mediating their real-world use. • Patient Engagement: AI chatbots and monitoring apps enhance patient self-care and remote symptom tracking, with nurses guiding safe and contextual use. Nurses serve as translators, gatekeepers, and co-designers of AI systems, balancing alerts with clinical judgment while safeguarding patient privacy and ethical use. Regional variability in infrastructure and cultural attitudes toward AI affect adoption. AI has the potential to enhance, not replace, hematology nursing. Nurses must be empowered through training, involvement in AI system design, and ethical governance. As advocates for patient-centered care, nurses should lead AI integration efforts to ensure these technologies improve outcomes while upholding trust, empathy, and equity. Future AI innovation in hematology must be shaped by nursing insight to remain clinically meaningful and ethically grounded.