Medicare and Medicaid Healthcare Access and Affordability Using Agentic Generative AI and AGI: Policy Implications and Guidelines

The United States' public health insurance programs, Medicare and Medicaid, face persistent challenges in ensuring equitable access to care and containing escalating costs, with an estimated quarter of all healthcare spending lost to administrative inefficiency. The emergence of advanced artificial intelligence, particularly Agentic AI and Generative AI (GenAI), presents a paradigm-shifting opportunity to address these systemic issues. Agentic AI, characterized by its ability to perform complex, multi-step tasks autonomously with human oversight, moves beyond mere automation to enable intelligent reasoning and workflow management. This paper explores the transformative potential of these technologies in streamlining administrative burdens, enhancing clinical decision support, personalizing member engagement, and optimizing resource allocation. We analyze specific use cases—including automated eligibility verification, prior authorization, and claims processing—and quantify the substantial economic impact and return on investment achievable through their implementation. Furthermore, we critically examine the significant policy implications, including algorithmic bias, regulatory compliance, data privacy, and the necessity for human-in-the-loop oversight. The paper concludes with a set of proposed guidelines and concrete policy recommendations for lawmakers and regulators to ensure the ethical, equitable, and effective deployment of Agentic and Generative AI, ultimately aiming to expand access and improve affordability for millions of beneficiaries.