JISARA

Abstract: The rapid adoption of generative artificial intelligence (GenAI) technologies, healthcare organizations aiming to leverage these advancements often need help scaling their personnel and infrastructure. Amazon Web Services (AWS) and Microsoft Azure are leading cloud service providers. This study aims to analyze and compare the generative AI offerings from AWS and Azure. AWS offers robust generative AI tools like Amazon SageMaker, while Microsoft Azure counters with Azure Machine Learning. We comprehensively review their capabilities and potential to enhance organizational maturity in operational efficiency and innovation capacity within the health insurance sector. Utilizing the maturity model within the NIST Cybersecurity Framework (CSF) 2.0, we will evaluate how generative AI solutions from these cloud platforms can contribute to improving healthcare organizational maturity. Our methodology encompasses a framework proposal for analyzing Generative AI technologies, a review, and a comparative analysis between AWS and Microsoft technologies . This ensures a robust integration with NIST CSF 2.0, specifically addressing healthcare organizations' needs. We perform an in-depth examination of case studies, industry reports, and existing literature to provide a nuanced understanding of each platform's strengths and weaknesses. We will also consider cost, ease of use, scalability, and integration with existing healthcare systems. With this research, we aim to provide valuable insights to IT managers and AI practitioners looking to implement generative Artificial Intelligence effectively within their healthcare organizations. The research question for this paper is: how do AWS and Microsoft Azure capabilities differ in generative AI capabilities and features, and how can these differences impact organizational maturity in the healthcare industry, as defined by the NIST 2.0 framework? Our analysis has shown that both AWS and Azure offer foundational solutions capable of supporting the deployment of GenAI in health insurance organizations, each with distinct strengths.

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Recommended Citation: Taylor, E., Zhou, S., Garcia, J., Cherry, B., Chung, S., (2026). Evaluating AWS vs. Azure for Generative AI in Healthcare: A Comparative Analysis Using the NIST CSF 2.0 Maturity Model. Journal of Information Systems Applied Research and Analytics 19(4) pp 26-37. https://doi.org/10.62273/SHFC3950