This systematic review explores the impact of artificial intelligence (AI) on clinical risk management and patient safety in healthcare. The study analyzed 36 articles published between 2013 and 2023, focusing on AI applications in three main clinical risk domains: clinical processes, healthcare-associated infections, and medication errors. Additionally, the review examined the role of AI in incident reporting, a critical component of patient safety. AI has the potential to enhance patient safety by improving the identification of errors and facilitating the prevention of adverse events. It can be applied in various ways, such as through automated systems for detecting stroke and cancer, reducing medication errors, and improving the accuracy of diagnostic processes. AI also supports incident reporting by analyzing data to identify trends and improve the efficiency of reporting systems. However, the use of AI in clinical risk management requires human supervision and cannot replace human skills entirely. The review highlights the importance of integrating AI with existing risk management practices and emphasizes the need for standardized frameworks, such as the International Classification for Patient Safety (ICPS), to categorize and analyze adverse events. The study concludes that AI can be a valuable tool in enhancing patient safety and clinical risk management, but its implementation must be carefully managed to ensure effectiveness and safety. The findings suggest that AI should be used in conjunction with human expertise to optimize outcomes and reduce risks in healthcare settings.This systematic review explores the impact of artificial intelligence (AI) on clinical risk management and patient safety in healthcare. The study analyzed 36 articles published between 2013 and 2023, focusing on AI applications in three main clinical risk domains: clinical processes, healthcare-associated infections, and medication errors. Additionally, the review examined the role of AI in incident reporting, a critical component of patient safety. AI has the potential to enhance patient safety by improving the identification of errors and facilitating the prevention of adverse events. It can be applied in various ways, such as through automated systems for detecting stroke and cancer, reducing medication errors, and improving the accuracy of diagnostic processes. AI also supports incident reporting by analyzing data to identify trends and improve the efficiency of reporting systems. However, the use of AI in clinical risk management requires human supervision and cannot replace human skills entirely. The review highlights the importance of integrating AI with existing risk management practices and emphasizes the need for standardized frameworks, such as the International Classification for Patient Safety (ICPS), to categorize and analyze adverse events. The study concludes that AI can be a valuable tool in enhancing patient safety and clinical risk management, but its implementation must be carefully managed to ensure effectiveness and safety. The findings suggest that AI should be used in conjunction with human expertise to optimize outcomes and reduce risks in healthcare settings.