Artificial Intelligence Applications in Nursing and Clinical Decision-Making: A Review

Abstract

Background: The increasing use of artificial intelligence (AI) in healthcare has created new opportunities to support clinical decision-making and improve the quality of care. In nursing practice, AI technologies are being adopted to assist with patient monitoring, risk assessment, and workflow management.

Aim: The aim of this review is to analyze the role of AI in nursing practice, with emphasis on its applications in clinical decision-making,
impact on patient outcomes, and challenges to implementation.

Methods: A narrative review of the literature was reported using Google Scholar to identify peer-reviewed articles related to AI, nursing practice, and clinical decision support systems (CDSSs). Relevant studies were selected according to predefined inclusion and exclusion criteria and synthesized thematically.

Findings: The review highlights the use of key AI technologies in nursing, including machine learning, natural language processing, expert systems, and robotics. CDSSs were commonly reported as effective tools for supporting nursing decisions related to patient safety, early warning systems, and care planning. AI applications were associated with improved quality of care, reduced errors, and enhanced nursing efficiency. However, challenges such as data quality issues, lack of interoperability, limited AI literacy among nurses, and concerns related to usability and trust were frequently reported.

Conclusion: AI has the potential to enhance nursing practice and clinical decision-making. Strengthening education, improving system design, and addressing implementation barriers are essential for the successful integration of AI into nursing care.