Abstract
BACKGROUND: Artificial intelligence (AI) is a rapidly evolving technology with the potential to revolutionize the health care industry. In Saudi Arabia, the health care sector has adopted AI technologies over the past decade to enhance service efficiency and quality, aligning with the country's technological thrust under the Saudi Vision 2030 program. OBJECTIVE: This review aims to systematically examine the impact of AI on health care quality in Saudi Arabian hospitals. METHODS: A meticulous and comprehensive systematic literature review was undertaken to identify studies investigating AI's impact on health care in Saudi Arabia. We collected several studies from selected databases, including PubMed, Google Scholar, and Saudi Digital Library. The search terms used were "Artificial Intelligence," "health care," "health care quality," "AI in Saudi Arabia," "AI in health care," and "health care providers." The review focused on studies published in the past 10 years, ensuring the inclusion of the most recent and relevant research on the effects of AI on Saudi Arabian health care organizations. The review included quantitative and qualitative analyses, providing a robust and comprehensive understanding of the topic. RESULTS: A systematic review of 12 studies explored AI's influence on health care services in Saudi Arabia, highlighting notable advancements in diagnostic accuracy, patient management, and operational efficiency. AI-driven models demonstrate high precision in disease prediction and early diagnosis, while machine learning optimizes telehealth, electronic health record compliance, and workflow efficiency, despite adoption challenges like connectivity limitations. Additionally, AI strengthens data security, reduces costs, and facilitates personalized treatment, ultimately enhancing health care delivery. CONCLUSIONS: The review underscores that AI technologies have significantly improved diagnostic accuracy, patient management, and operational efficiency in Saudi Arabia's health care system. However, challenges such as data privacy, algorithmic bias, and robust regulations require attention to ensure successful AI integration in health care.