THE ROLE OF ARTIFICIAL INTELLIGENCE IN TRANSFORMING EVIDENCE-BASED NURSING PRACTICE

Abstract

Artificial Intelligence (AI) has rapidly emerged as a transformative force in healthcare, particularly within the domain of nursing. As evidence-based practice continues to evolve, AI technologies present new avenues for optimizing patient care, improving clinical decision-making, enhancing workflow efficiency, and supporting professional development among nurses. However, the integration of AI into nursing practice also introduces a host of ethical, practical, and systemic challenges. This systematic review aims to evaluate the role of AI in transforming evidence-based nursing practice by synthesizing recent literature on AI applications, impacts on nursing outcomes, and ethical considerations. The aim of the study is to explore how AI technologies influence evidence-based nursing practices and to identify key benefits, limitations, and ethical challenges associated with their integration. Study objectives. 1. To investigate how AI supports clinical decision-making, predictive analytics, and workflow optimization in nursing practice. 2. To evaluate the effects of AI integration on nurse satisfaction, education, training, and patient outcomes. 3. To identify the ethical challenges associated with AI implementation in nursing, including data privacy, algorithmic bias, informed consent, and accountability. 4. To provide evidence-based recommendations for the ethical and effective integration of AI into nursing practice. The object of research. The object of the study includes peer-reviewed journal articles and systematic reviews published between 2013 and 2025 that address AI technologies used in nursing practice and education. The subject of research. The subject of the study is the role of artificial intelligence in transforming nursing practice, decision-making, and the ethical dimensions of care delivery in modern healthcare settings. The methods of study included a systematic review of literature using PRISMA guidelines. Database searches were conducted in PubMed, CINAHL, Scopus, and Web of Science using predefined inclusion and exclusion criteria. The analysis focused on AI applications in nursing, measurable outcomes, and ethical considerations. Studies were selected based on relevance, methodological rigor, and alignment with the research objectives. The scientific and practical value of the study. This review synthesizes the current evidence on AI’s transformative potential in nursing practice and highlights both the opportunities and risks associated with its adoption. It serves as a resource for nurse leaders, policymakers, and educators by offering actionable insights into how AI can be ethically and effectively implemented to enhance care delivery, patient safety, and nursing education. The findings of this systematic review indicate that AI contributes significantly to improving diagnostic accuracy, predicting patient deterioration, and streamlining administrative tasks. AI-based decision support systems and predictive tools enhance nurses’ ability to make timely and evidence-based clinical decisions. Educational technologies powered by AI facilitate nurse training, continuing education, and simulation-based skill development. Moreover, AI supports workflow optimization by automating repetitive tasks, thereby increasing nurse efficiency and reducing burnout. However, ethical concerns remain a central challenge. Issues of data privacy, algorithmic bias, transparency, and nurse autonomy must be addressed through rigorous ethical frameworks and institutional safeguards. The review underscores the need for nurses to participate in the design, deployment, and evaluation of AI tools to ensure these technologies align with core nursing values and patient-centered care principles.