Revolutionizing Healthcare: The Challenges & Role of Artificial Intelligence and Machine Learning in Healthcare Management Practice

Abstract

The integration of Artificial Intelligence (AI) and Machine Learning (ML) in healthcare is transforming traditional management practices, offering the potential to enhance clinical outcomes, streamline operations, and optimize resource allocation. This revolution, however, is not without significant challenges. Issues such as data privacy, algorithmic bias, lack of standardization, resistance to technological adoption, and limited interpretability of AI models pose critical barriers to successful implementation. This paper explores the evolving role of AI and ML in healthcare management, focusing on their applications in diagnostics, patient care, predictive analytics, and administrative decision-making. It also examines the systemic challenges that hinder their effective deployment and suggests strategies to overcome them. By analyzing current advancements and evaluating real-world case studies, this research contributes to a deeper understanding of how AI and ML can be harnessed to create resilient, efficient, and patient-centric healthcare systems.