As healthcare organizations recognize the need to improve operational efficiency, ease clinical workflows, and enhance patient care and experience, they are increasingly turning to artificial intelligence. However, many organizations don’t have the proper infrastructure to support AI initiatives.
The 8th Annual Nutanix Healthcare Vertical Enterprise Cloud Index dives into healthcare’s current interest and preparedness related to AI. The report points out challenges including infrastructure readiness and shadow AI, plus other trends around containerization.
HealthTech spoke with Scott Ragsdale, vice president of sales for healthcare and SLED at Nutanix, about his biggest takeaways from the report and how healthcare organizations can navigate this space going forward.
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HEALTHTECH: What were some of the biggest findings from the report and what do they mean for healthcare organizations?
RAGSDALE: The biggest takeaway for me is that healthcare organizations are embracing AI at a fast pace, but their infrastructure isn’t evolving to keep up with it. It’s well known that healthcare has a lot of technical debt. Overcoming that to take on these new AI workloads is the biggest challenge for organizations. Eighty-eight percent of healthcare leaders told us their current infrastructure isn’t fully ready to support AI deployment, and it’s evident.
87%
The percentage of IT executives who believe that the use of AI tools and agents outside of official oversight creates business risk
Source: Nutanix, 8th Annual Nutanix Enterprise Cloud Index, June 2026
HEALTHTECH: According to the report, shadow AI is a major concern among healthcare leaders. How can organizations address shadow AI without hindering innovation?
RAGSDALE: It’s important to recognize that shadow AI is a symptom; it’s not the root problem. Clinicians, researchers and business users are all looking for ways to solve problems quicker and faster to improve outcomes for patients. If they can’t get what they need, they’re going to go out and download something that is unsanctioned or unsupported by the organization. The answer isn’t to hinder innovation; the answer is to create governed environments where innovations can happen safely. I think that’s the real challenge. Healthcare organizations need to adopt approved AI platforms and have clear policies around their usage.
HEALTHTECH: Interest in and use of containerization in healthcare is on the rise. Why does it play such an important role in deploying AI models, and what do healthcare organizations need to know to implement containerization successfully?
RAGSDALE: Containers are becoming the foundation of modern AI applications because they provide portability, scalability and consistency across the environment. AI workloads need to run wherever data is generated, which could mean being in patient rooms. Containerization makes scalability and simplicity possible.
83%
The percentage of IT executives whose organizations are building new applications in containers
Source: Nutanix, 8th Annual Nutanix Enterprise Cloud Index, June 2026
HEALTHTECH: The report states that 88% of healthcare leaders view their current infrastructure as not fully ready to support AI deployment on-prem. What can organizations do to improve their readiness?
RAGSDALE: The first step is recognizing that AI readiness isn’t about going out and buying a bunch of GPUs and sticking them in the data center. It’s about modernizing the entire operating model. Healthcare organizations need infrastructure that can support hybrid environments, manage data consistently and provide strong governance to run AI workloads where it makes the most sense. Maybe that’s in patient rooms, or maybe it’s in data centers — wherever that happens to occur.
They also need to address the legacy infrastructure and technical debt that we talked about. Healthcare organizations have got to improve data governance, adopt standardized platforms and create modern application strategy built around containers and cloud-native technologies. Most important, they need a strategy that supports AI inference at the point of care, such as patient rooms, where real-time insight can directly influence patient outcomes. In many cases, those clinicians can see more patients using AI. They’re doing less manual transcription of notes and summaries into the electronic health record, enabling them to see more patients.
HEALTHTECH: While a majority of respondents see potential for AI agents, under 60% seems lower than expected considering growing discussions around the topic. What does that say about where healthcare organizations are now in their AI journeys?
RAGSDALE: I actually view those numbers as a sign of maturity and not skepticism. Healthcare has always approached transformative technologies carefully because the stakes are so high in healthcare. Patients’ lives and outcomes are on the line. They have to be very careful about what they adopt. Healthcare doesn’t move on hype; it moves based on evidence, governance and trust.
I’d say the fact that more than half the respondents already expect AI agents to improve productivity, and all of the goodness that comes along with that, is significant. At the same time, healthcare leaders, such as the CIOs we’ve talked to, want to understand governance, clinical validation, security and accountability, and what that means for regulations like HIPAA.
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HEALTHTECH: Were any of the report’s findings surprising to you, and why?
RAGSDALE: I’d say the shadow AI one was probably the most striking. The report states that nearly four out of five healthcare organizations reported AI tools or agents being deployed outside of IT oversight. That tells me that the demand for the AI capabilities is growing much faster than the organizations can govern and adopt policies.
The other finding that stands out is the combination of the optimism around AI that we talked about and the acknowledgement that infrastructure readiness remains a challenge. I’d say organizations see the opportunity and understand that AI can improve operational efficiency clinical workloads and patient outcomes, but they also recognize that achieving those benefits requires modernization, governance and strong infrastructure.
If there’s one thing that the report reinforces, it’s that the future of AI in healthcare is going to be hybrid. It’s going to be in the cloud, containerized, in the data center and living in multiple different constructs. It will be pervasive. AI has to be at the point of care in the patient rooms.
HEALTHTECH: What is the biggest takeaway healthcare organizations should get from this report?
RAGSDALE: The biggest takeaway is that healthcare organizations need to be deliberate about how they adopt AI. Unlike some previous technology trends, where organizations could deploy a platform and figure out the use cases later, AI requires a clearly defined problem, measurable outcomes and thorough testing to ensure it delivers the expected results.
One of the most telling findings in the report is that 88% of healthcare leaders believe their current infrastructure is not fully ready to support AI deployment on-premises, while nearly 80% report concerns around shadow AI and the risks associated with unmanaged AI initiatives. Those findings tell me that the industry recognizes the potential of AI, but many organizations are still building the operational, governance and infrastructure foundations needed to scale it successfully.
My advice is to start with a specific business or clinical challenge, establish clear success criteria and validate outcomes through a controlled pilot. Learn from peers who are already further along in their AI journey, leverage industry expertise where appropriate and focus on delivering measurable value before expanding to broader use cases. Organizations that take that disciplined approach will be much more likely to achieve meaningful outcomes and avoid the pitfalls that often accompany emerging technologies.
