Healthcare organizations are racing to adopt AI faster than their technology foundations can support, according to a new survey from enterprise cloud company Nutanix.
The research found 88% of healthcare IT professionals believe their current infrastructure is not fully prepared to support on-premises AI workloads. More than 80% expect application containerization to increase, and leaders flagged shadow AI, governance and hybrid infrastructure as growing concerns.
Nutanix chief AI officer Debo Dutta said healthcare data at the edge is growing exponentially as patient monitoring, clinical diagnosis and robotic surgery generate more information. Before AI can shift from pilots to enterprise-wide deployment, organizations will need to solve for latency and governance in clinical environments.
Containers are central to the argument: they let AI models run at the bedside for real-time processing instead of depending on cloud-only deployment. Organizations increasingly balance workloads across on-premises systems, private clouds and public cloud services.
For CIOs, the findings suggest the next phase of AI adoption depends less on choosing the newest model and more on modernizing the underlying technology stack.
