Optimizing Patient Flow and Resource Allocation in Hospitals using AI

The present study investigates the incorporation of artificial intelligence (AI) into healthcare administration, with a specific focus on optimizing patient flow as well as allocating resources in various hospital environments. Using a descriptive research methodology with secondary data gathering, the study adopts an interpretivist philosophy and a deductive technique. The findings show that applying AI-driven techniques significantly improves patient wait times, the efficiency of resource utilization, and patient outcomes. The contrast between AI-enhanced practices and traditional procedures demonstrates how much better they are at optimizing patient flow. On the other hand, implementation-critical elements include initial investment expenses and ethical considerations. Investing in AI infrastructure, resolving algorithmic biases, including protecting data privacy are among the recommendations. Future research ought to concentrate on the scalability, long-term effects, and enhancements to AI systems for objective forecasts