For various reasons, artificial intelligence (AI) in the medical sector is fast changing from a luxury to a need. Analyzing health data with conventional techniques becomes difficult given its rising bulk. More exact and faster medical decisions are made possible by AI's fast and accurate processing of enormous volumes of data. For radiology, for instance, artificial intelligence has been applied to raise diagnostic accuracy—especially in relation to cancer detection. AI improves radiographical interpretation accuracy in diagnosis. AI has enhanced diagnosis rates in breast cancer by up to 30 percent by helping to spot trends or early indicators that human professionals might overlook and therefore help to lower unnecessary procedures. AI can ease strain on healthcare professionals by automating routine duties like medical image processing or scheduling, therefore freeing clinicians to concentrate more on direct patient care in view of the worldwide medical personnel shortage. Healthcare institutions in Saudi Arabia are incorporating AI chatbots and virtual assistants to handle administrative duties like appointment scheduling and answering basic questions. AI also supports the creation of customized treatment regimens matched to individual patient data, including genetics and medical history, therefore producing better outcomes and less treatment side effects. In oncology especially, where tailored treatment plans might raise survival rates, this is especially important. For example, by streamlining cancer treatment paths with artificial intelligence, a U.S. healthcare provider saved $91 million yearly. Also, early interventions can be planned thanks to AI-powered predictive analytics that can predict disease risks or a patient's probability of deterioration. There has been a 20 percent decrease in patient readmissions in U.S. hospitals that have implemented AI-driven predictive analytics. Beyond only medical management, artificial intelligence is very important for improving operational effectiveness and cost-cutting in hospitals, hence improving resource management. Data analysis and appointment scheduling are two examples of the streamlined tasks that might reduce expenses by as much as 20 percent. In addition to helping with bed availability management, AI helps patient flow management by forecasting when patients will be discharged. AI enables hospitals to more successfully get ready for new patients by examining patient conditions and hospital statistics. For instance, Cleveland Clinic has applied artificial intelligence to enhance discharge planning, therefore lowering patient waiting times and raising general hospital capacity. Since AI can forecast future demand for medications and medical equipment, thereby enabling hospitals to keep ideal inventory levels, it also has a major influence on supply chain management. AI automates medical supply ordering at some U.S. hospitals, therefore lowering the risk of understocking or overstocking crucial items. Locally, thanks to considerable efforts by the Saudi government, as the Kingdom is placed 14th globally and first in the Arab world in the global artificial intelligence index endorsed by the United Nations, represented by the Advisory Board for Artificial Intelligence, out of 83 countries. Massive advancements in AI technology and its implementation across various sectors, particularly healthcare, are anticipated as a result of the ambitious Vision 2030 and the serious initiatives of the Saudi Data and Artificial Intelligence Authority (SDAIA). Recognizing that data is the oil of the future is a critical step in the right direction.
