Abstract: The integration of data analytics, artificial intelligence (AI), and cloud computing has significantly transformed the healthcare sector, particularly in optimizing Medicaid services. This paper explores various AI-driven solutions in predictive analytics, data quality, interoperability, workforce training, and data-driven decision-making. By leveraging the latest research, we examine advancements in AI-assisted diagnostics, personalized patient care, and innovative Medicaid cost optimization strategies. Furthermore, we discuss the ethical and operational challenges of AI in healthcare, ensuring a balanced perspective on its dual impact. The study provides a comprehensive overview of how AI can enhance efficiency, reduce costs, and improve healthcare outcomes while addressing the potential risks and necessary policy considerations for its widespread implementation.
Keywords: Artificial Intelligence (AI), Data Analytics, Cloud Computing, Medicaid Optimization, Predictive Analytics, Healthcare Interoperability, AI in Healthcare, Machine Learning, Healthcare Data Management, AI Ethics, Workforce Training, AI-Driven Decision-Making, Cost Optimization, Healthcare Automation, Blockchain in Healthcare, IoT in Healthcare.
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DOI:
10.17148/IJARCCE.2025.14273
