Paper Title
Optimizing Revenue Cycle Management in Healthcare: AI and It Solutions for Business Process Automation

Abstract
Revenue Cycle Management (RCM) stands as an essential healthcare financial element since it manages efficient claim handling combined with payment receipt processes that optimize organizational profits. The conventional RCM operational model suffers from multiple difficulties including inefficiencies, administrative burdens and regular billing mistakes that eventually generate revenue loss and operational delays. This paper investigates the potential of IT and AI solutions to transform RCM operations by streamlining procedures and boosting financial projection quality as well as improving claim verification. The research bases its analysis on real-life implementations of artificial intelligence-based billing automation in addition to robotic process automation (RPA) and predictive analytics solutions in healthcare finance domain. An AI-driven automated system decreases denials processing and speeds up payment times while improving financial performance which enhances healthcare service efficiency. The implementation of blockchain technology as an information technology solution improves both security and interoperability within healthcare financial systems. The ongoing challenges for healthcare organizations include the cost of implementation along with workforce transitioning issues and privacy-related difficulties with data. The research findings demonstrate why healthcare organizations need to implement strategic AI and IT solutions for improving their Revenue Cycle Management systems. Research should focus on how AI systems connect with value-based healthcare approaches for maximum financial performance improvement. Keywords - AI in Healthcare, Revenue Cycle Management, Business Process Automation, IT Solutions, Healthcare Finance