Nutanix has released new insights from its eighth annual Enterprise Cloud Index (ECI) survey, focusing on the healthcare, financial services, and public sector industries.
This sector-specific research complements the global report, highlighting the evolving infrastructure strategies organisations are employing to accommodate AI's expanding role. Despite the rise in AI adoption within these sectors, Nutanix's study indicates that many organisations identify gaps in their existing infrastructure, challenging the scalability of AI workloads.
The ECI survey sheds light on the amplified challenges faced by regulated sectors such as healthcare, financial services, and the public sector, compared to the global industrial average. These industries encounter distinct hurdles, including shadow AI risks and data sovereignty issues, largely due to stringent regulations. Such challenges are intensifying organisational silos, evolving them into compliance risks, as these sectors strive to update their hybrid multicloud environments to support AI applications effectively.
Nutanix EVP of Product Management, Thomas Cornely, highlights the varied infrastructure demands across different sectors, emphasising the need for flexibility, resiliency, and security to scale both traditional and AI-powered applications. Shadow AI, where AI technologies are implemented outside of approved IT protocols, remains a significant concern, exacerbating the gap between IT governance and business demands, especially in regulated industries.
Healthcare organisations are moving AI workloads closer to patient care, with application containerisation playing a crucial role in minimising cloud latency and safeguarding data sovereignty. Nutanix's Healthcare Report reveals 72% of healthcare IT leaders prioritise data sovereignty in their infrastructure needs, while 83% express concern over shadow AI. Preferred AI applications in the near future include generative AI, agentic AI, and predictive analytics, highlighting the sector's commitment to enhancing patient care and operational efficiency through technology.
In financial services, AI is widely used to optimise system operations, from customer service to fraud detection. Nutanix's report shows an overwhelming consensus among financial executives regarding the risks posed by shadow AI. Despite data sovereignty being a top priority, only 62% utilise public cloud solutions, with a significant reliance on containerisation to ensure regulatory compliance while meeting performance demands.
Public sector entities are adopting AI to drive mission success and secure public data concurrently. However, infrastructure readiness remains a critical issue, with Nutanix findings indicating that 73% of public sector systems are not prepared for complex on-premise AI workloads. Shane McDaniel from the City of Seguin underscores the importance of a balanced approach to AI implementation, focusing on infrastructure modernisation and clear governance frameworks to manage innovation without compromising security.
In summary, Nutanix's eighth annual ECI survey highlights the infrastructural challenges and opportunities for AI integration across highly regulated industries. The findings underscore a growing need for robust, hybrid multicloud solutions to manage AI's deployment at scale while adhering to stringent regulatory requirements. To access the full insights and data from the ECI survey, readers can download the industry-specific reports available online.
Nutanix, a pioneer in hybrid multicloud computing, unveils new regulated industry data from its eighth annual Enterprise Cloud Index (ECI) survey and research report shared earlier this year. Serving as a deep-dive companion to the global report, the Healthcare, Financial Services, and Public Sector industry reports reveal how organisations are adapting infrastructure strategies to support growing AI adoption.
Nutanix’s ECI survey indicates that enterprise AI adoption is accelerating across healthcare, financial services, and public sector organisations, but many reported that their infrastructure is not ready to run these workloads at scale. The report identified concerns around shadow AI risks, data sovereignty, compliance, and organisational silos as organisations work to modernise hybrid multicloud environments for AI applications.
Highly regulated sectors
While Nutanix’s global ECI survey illustrated a baseline of challenges with AI infrastructure readiness among IT decision-makers, these new analyses reveal that the pressure is significantly magnified within these highly regulated sectors.
Enterprise AI adoption is accelerating rapidly across healthcare, financial services, and public sector organisations, yet IT leaders in these fields report a much sharper infrastructure deficit. Because of strict regulatory mandates, these specific industries face heightened exposure to shadow AI risks and data sovereignty violations compared to the global average, transforming generic organisational silos into critical compliance vulnerabilities as they attempt to modernise hybrid multicloud environments.
Approved IT governance
“Organisations across every industry are working to move their AI projects from experimentation to delivering real business value, but the infrastructure requirements vary significantly depending on sector and workload,” said Thomas Cornely, EVP of Product Management at Nutanix. “The one consistent factor is a need for infrastructure and operating models that deliver flexibility, resiliency, and security to run both traditional and AI-powered applications at scale.”
The rise of shadow AI, when employees or business units use AI tools outside approved IT governance or security oversight, is an ongoing concern that highlights governance gaps in these highly regulated industries. Additionally, organisational silos between business units and IT teams add to the potential complexity of AI use and governance.
Primary operational hurdle
Key findings from this year’s report by industry, based on survey responses, include:
- As healthcare organisations transition AI workloads directly to the bedside, application containerisation has become foundational to supporting this innovation by providing secure, portable environments that eliminate cloud latency and protect data sovereignty. However, balancing these modern deployments with general on-premises infrastructure readiness remains the industry's primary operational hurdle.
- According to the Nutanix ECI Healthcare Report, 72% of healthcare IT leaders cite data sovereignty as a top infrastructure priority.
- Data from the Nutanix study reveals that 83% of healthcare organisations view unauthorised "shadow AI" tools as a critical business and data risk.
- The Nutanix ECI study revealed the top AI applications or capabilities healthcare organisations expect to use within the next three years include generative AI (62%), agentic AI or autonomous agents (57%), and predictive analytics or machine learning models (55%).
Meeting regulatory requirements
AI adoption in healthcare is accelerating, driven by the need to improve operational efficiency, enhance patient outcomes, and support innovation in both clinical and administrative workflows. However, challenges such as infrastructure readiness, shadow AI, and operational barriers remain significant. Containers are playing a key role as healthcare organisations seek to support innovation while protecting sensitive patient data and meeting regulatory requirements.
"As we expand facilities and scale modern applications, our underlying infrastructure must deliver localised performance and resilience without compromising patient data privacy. Healthcare organisations are feeling increasing pressure to support AI workloads while ensuring governance, security, and operational consistency across the environment. To enable AI safely at the point of care, organisations must break down silos, align technology and clinical workflows, and maintain clear control over how sensitive data is managed. Utilising a hybrid approach, anchored by Nutanix, can help lean IT teams simplify operations while balancing innovation, compliance, and performance," said Benjamin Urquhart, Chief Technology Officer, Five Horizons Health Services.
Data sovereignty requirements
Financial institutions are aggressively deploying AI to optimise everything from core systems to edge operations, including in-branch personalisation, customer service, anomaly detection, and more. However, strict data sovereignty requirements are forcing a shift toward secure, hybrid cloud architectures.
- The Nutanix Financial Services ECI Report found that 86% of financial sector executives believe unmanaged shadow AI tools introduce severe business risk.
- Research from the Nutanix study indicates that 62% of financial services IT leaders expect conversational and agentic AI to materially improve customer or employee experiences.
- According to Nutanix’s report, 90% of financial services IT leaders report AI is meaningfully accelerating container adoption.
Supporting AI adoption
While financial services organisations continue to improve infrastructure to support AI adoption, data protection and other concerns limit public cloud use to just 62% despite 79% citing data sovereignty as a high priority or must-have factor. Containers and hybrid infrastructure are emerging as critical components needed for scaling AI responsibly to support high-performance workloads from core systems to the edge, including in-branch personalisation, point-of-sale anomaly detection, and predictive ATM maintenance.
“AI has the potential to transform how we support our families in the homebuying journey, but to truly deliver on that promise, we must bridge the gap between innovation and operational reality. By leveraging agentic AI within a secure, hybrid environment, we are streamlining our mortgage processes while maintaining the high standards of governance and trust our customers expect. This approach allows us to scale our technology footprint with the flexibility needed to stay ahead in a highly regulated industry,” said Dr. Caleb Ondrusek, EVP Technology and Innovation, Fairway Home Mortgage.
Public sector infrastructure
Faced with a dual mandate to advance mission outcomes and safeguard public data, government agencies are turning to application containerisation to improve the speed, scalability, and security of their AI workloads, even as organisational silos increase the risk of unmanaged shadow AI.
- Government and education IT leaders surveyed in the Nutanix Public Sector Report overwhelmingly agree (91%) that unvetted AI usage creates severe mission and security risks.
- A key takeaway from the Nutanix ECI research is that 73% of public sector infrastructure is currently unready to run complex AI workloads on-premises.
- Findings from the Nutanix industry study indicate that 87% of public sector technology leaders expect their reliance on application containerisation to scale up over the next three years.
Public sector organisations
The findings show that public sector organisations, including federal, state, and local governments, K-12, and higher education, are incorporating AI into business operations ranging from benefits eligibility to fraud detection. Yet, they are facing barriers in infrastructure readiness, workforce capability, and governance. This drives the urgent need for public sector IT leaders to build modernised hybrid infrastructure that can support the growing needs of this diverse industry.
"Our people are our greatest asset, and they're naturally drawn to tools that help them serve our community better. At the City of Seguin, we embrace AI as a force multiplier for that mission. But enthusiasm without guardrails creates risk, and shadow AI isn't just a security concern; it's a governance gap. Our focus has been on modernising our infrastructure and building the culture and clear digital policies that channel our team's innovation energy in the right direction, so our staff can innovate confidently within a secure, compliant framework that works for the mission, not against it,” Shane McDaniel, Chief Information Officer, City of Seguin, Texas.
GenAI application deployment
For the eighth consecutive year, Nutanix commissioned a global research study to assess the state of cloud adoption, containerisation, and GenAI application deployment. Conducted in November 2025 by Wakefield Research, the survey gathered responses from 1,600 cloud, IT, and engineering executives with at least a manager-level title.
Respondents represent organisations with 500 or more employees across Australia, Brazil, France, Germany, India, Italy, Japan, Mexico, the Netherlands, the Kingdom of Saudi Arabia, Singapore, Spain, the United Kingdom, and the United States. To learn more about the report and findings, please download the full eighth annual ECI report or industry specific reports here.
