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The integration of Artificial Intelligence (AI) in healthcare presents a promising avenue for revolutionizing patient care and operational processes. This paper presents a comprehensive theoretical framework aimed at facilitating the seamless integration of AI technologies within the healthcare sector. The development of this framework involved an extensive synthesis of existing literature encompassing AI applications in healthcare, technology integration frameworks, and operational strategies. Leveraging insights from established practices and emerging trends, the framework devised offers a structured approach elucidating the strategic incorporation of AI in diverse healthcare domains. The proposed framework emphasizes personalized patient care, clinical decision support, predictive analytics, and operational streamlining through AI adoption. Key considerations such as ethical guidelines, regulatory compliance, interoperability, and scalability are integrated into the framework to ensure successful AI implementation in healthcare settings. Furthermore, the framework delineates implementation strategies, stakeholder engagement models, and a roadmap for the adoption and iterative refinement of AI-driven solutions within healthcare institutions. This research contributes a comprehensive theoretical framework tailored to optimize the assimilation of AI technologies in healthcare, aiming to enhance patient outcomes, operational efficiency, and pave the way for future advancements in AI-enabled healthcare systems.