Research on AI-Embedded To-Be Processes and Modern Hospital Management

Abstract

With the rapid development of artificial intelligence (AI) technologies, the healthcare industry is accelerating its transformation toward intelligent and digitalized systems. The To-be process, as an important tool for designing future ideal business models, provides a structural framework for the systematic application of AI in hospital management. This study focuses on the implementation pathways and managerial value of embedding AI into To-be processes, and analyzes its role in improving operational efficiency, optimizing resource allocation, and promoting the transformation of management models. The results indicate that AI integration into To-be processes produces significant effects at three levels. First, at the operational level, intelligent triage, automated scheduling, and process coordination mechanisms shorten patient waiting times and improve the efficiency of connections between clinical and administrative processes. Second, at the resource allocation level, data analytics and predictive models enable dynamic scheduling and refined management of medical resources, improving equipment utilization and workforce allocation. Third, at the management model level, AI facilitates the transformation of hospitals from experience-driven management to data-driven and intelligent decision-making management, enhancing the scientific basis and responsiveness of managerial decisions. Deep integration of AI into To-be processes helps promote the transition of hospital management from traditional experience-based approaches to data-driven and intelligent collaborative models.