Eighty-eight percent of healthcare IT leaders view their current infrastructure as not fully ready to support deploying AI workloads on-premises, according to the 2026 Nutanix Enterprise Cloud Index survey released today.
The report says the gap is significant because AI inference – the process of analysing data and generating results – is increasingly expected to occur at the point of care rather than solely in the cloud, helping reduce latency in clinical settings.
Single patient rooms can generate up to 7TB of data annually, and high-density device environments such as ICU beds can include 15 to 20 connected devices, requiring local, low-latency AI processing to maintain clinical continuity.
Nutanix, a leader in hybrid multicloud computing, published global findings from the healthcare vertical edition of its ECI survey, revealing a sector under mounting pressure.
“AI deployment is being driven from the top, shadow AI is proliferating across clinical and administrative functions, and the infrastructure required to support secure, compliant AI workloads at the point of care is not yet in place”.
Nutanix says healthcare organisations must prepare for AI workloads that operate at the bedside, where up to 75% of healthcare data is expected to be generated.
This shift introduces new operational barriers, including supporting low-latency processing for critical clinical decisions, managing distributed data environments, and integrating AI across hybrid systems while helping maintain patient safety or regulatory compliance.
While many IT leaders would prefer to deploy AI workloads on-premises to strengthen data control and compliance, organisations expect hybrid deployment models to remain common for the foreseeable future.
Daryush Ashjari, Nutanix Chief Technology Officer and VP of Solution Engineering, APJ, said, “Healthcare organisations across APJ are under growing pressure to adopt AI, but clinician demand is colliding with the readiness of the infrastructure underneath it. The impact extends beyond IT; it can affect the availability of critical systems, access to data, and ultimately, the continuity of patient care. For healthcare leaders, the priority is to shift from reactive management and build a unified, hybrid approach that bridges the gap between data sovereignty compliance and the real-time, low-latency insights required at the patient’s bedside.”
Key findings from the 2026 Nutanix Healthcare ECI report include:
- Shadow AI is widespread and largely unmanaged: Seventy-nine percent of healthcare organisations encounter AI applications or agents being implemented by employees in non-IT functions, and 83% believe that AI tools and agents operating outside official oversight create business risk. The same proportion, 83%, say silos between business units and IT make it difficult to effectively execute technology initiatives, deepening the governance challenge as AI adoption scales.
- AI is accelerating container adoption as healthcare modernises its application strategy: Eighty-six percent of healthcare organisations say AI is meaningfully accelerating their adoption of containers, which enable AI models to be deployed locally at the bedside in secure, portable environments. Eighty-one percent expect the level of application containerisation to increase at their organisation, and 80% are already building new applications in containers. Containers allow hospitals to keep data where it is generated, within their own walls, while enabling real-time AI-driven insights without compromising network performance.
- AI agents are seen as transformative for healthcare operations: Fifty-eight percent of healthcare IT leaders expect AI agents to improve productivity and efficiency, 57% anticipate agents will transform business processes and operations, and more than half (55%) see potential for AI agents to create new products, services, or revenue streams. Looking three years ahead, 57% of organisations anticipate using agentic AI or autonomous agents, alongside generative AI (62%) and predictive analytics or machine learning models (55%).
- Data sovereignty is a must-have, not a nice-to-have: Seventy-two percent of healthcare organisations say data sovereignty is a high priority or a must-include when making infrastructure decisions. Fifty-four percent run containerised applications on-premises or on private clouds today, and 54% feel the need to run infrastructure within a single country due to customer or stakeholder expectations. This reflects the sensitivity of protected health information (PHI) and the compliance requirements governing where this data can be stored and processed.
- AI adoption is being driven from the top, with scale coming fast: Fifty-five percent of healthcare organisations anticipate having more than five AI-enabled applications within three years, including 12% who expect to be running more than 10. Sixty-three percent currently run AI applications on managed service providers, with hybrid deployment models expected to remain the norm as organisations look to support AI centrally and at the point of care.
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