AI-Driven Decision-Making in Healthcare Administration: Exploring Predictive Models for Resource Allocation

Abstract

Artificial Intelligence now serves as a transformative healthcare management instrument which delivers advanced analytical features for decision support. Artificial Intelligence displays remarkable potential in healthcare resource distribution mechanisms for organizations. Through predictive modelling AI systems extract historical patterns to predict future requirements after which healthcare administrators can strategically allocate staff and medical supplies and equipment. This study investigates how AI-based decision making improves healthcare operational procedures while particularly examining predictive models for resource distribution management. AI technology enhances operational excellence while lowering healthcare expenditure while delivering superior patient care because assets are distributed using current requirements and forecast predictions. This research addresses data quality concerns alongside AI interoperability issues and ethical framework difficulties within healthcare administrative settings. The author demonstrates a path forward for AI model application in resource allocation which requires maintaining equilibrium between technological progress and human involvement.