This study investigates the transformative potential of artificial intelligence (AI) in revolutionizing electronic health records (EHRs) and compares the adoption rates and impacts in both public and private hospital settings. With the rapid advancement of AI technologies, there exists a significant opportunity to enhance the efficiency, accuracy, and accessibility of EHR systems, thereby improving patient care and outcomes. Through a comparative analysis of public and private hospitals, this research assesses the extent to which AI-driven EHR solutions have been implemented and integrated into healthcare practices. By examining factors such as infrastructure, investment, and regulatory frameworks, this study seeks to identify the drivers and barriers influencing AI adoption in each setting. Furthermore, this research evaluates the tangible benefits that patients derive from AI-enabled EHR systems. These benefits may include streamlined appointment scheduling, personalized treatment recommendations, predictive analytics for disease prevention, and enhanced communication between healthcare providers and patients. By leveraging AI algorithms, EHRs can efficiently process vast amounts of patient data, leading to more informed decision-making and proactive healthcare management. The findings of this study aim to provide valuable insights for policymakers, hospital administrators, and healthcare professionals seeking to optimize EHR systems through AI integration. By understanding the comparative advantages and challenges faced by both public and private hospitals, stakeholders can develop strategies to maximize the potential of AI in revolutionizing healthcare delivery and improving patient outcomes. Ultimately, this research contributes to the ongoing discourse on leveraging technology to address the evolving needs of modern healthcare systems.