Cloud Infrastructure Speeds the Next Phase of AI in US Healthcare

Cloud platforms are pushing AI deeper into US healthcare, offering scale and speed while forcing leaders to rethink security and governance

7 Jan 2026

Cloud computing has moved from a back-office concern to a strategic priority in US healthcare, as hospitals and health systems look to deploy artificial intelligence at scale.

The shift reflects the growing demands of modern AI tools, which require flexible and powerful computing resources to analyse medical images, automate billing and assist with clinical documentation. Traditional on-premise data centres often struggle to meet these needs, while cloud platforms allow organisations to expand or reduce capacity as required, lowering upfront investment and speeding deployment.

Surveys across the healthcare IT sector show adoption accelerating. More than 60 per cent of providers are already running workloads in the cloud or plan to expand their use in the near term, with AI cited as the main driver. Large systems such as Mayo Clinic and Providence have publicly pointed to cloud-based AI initiatives designed to improve diagnostics, streamline operations and enhance patient engagement.

Technology vendors are adjusting their strategies accordingly. Rather than promoting wholesale system replacements, they are emphasising partnerships and gradual adoption. Microsoft has positioned its cloud services as a secure foundation for healthcare data and analytics. Epic, the dominant electronic health record provider, has worked with cloud partners to make its software easier to deploy beyond traditional data centres, enabling customers to test AI tools such as clinical documentation assistance and predictive analytics without overhauling core systems.

The potential benefits are significant. Cloud-delivered AI can reduce administrative burdens, identify clinical risks earlier and extend advanced capabilities to smaller hospitals that previously lacked the resources of major academic centres. Industry analysts say this could slowly narrow the gap between large and mid-sized providers.

Concerns remain, however. Storing patient data in the cloud raises questions around cybersecurity, governance and compliance with the Health Insurance Portability and Accountability Act. While cloud providers offer encryption and regulatory frameworks, healthcare organisations retain responsibility for how systems are configured and managed. Weak data quality and poor interoperability between systems can also limit the effectiveness of AI tools.

Despite these challenges, momentum continues to build. Many healthcare leaders now view cloud infrastructure as a prerequisite for sustained AI adoption. Those that align technology, governance and strategy early may shape how care is delivered in the years ahead.