Executive Summary
The rise of data-driven operations and AI workloads is leading enterprises to rethink their plans to modernize infrastructure.
Under pressure to secure data and make it more portable, they are increasingly adopting containers to run AI-enabled applications. Looking ahead over the next three years, the vast majority (87%) of executives expect the level of application containerization within their organization to increase, according to a survey of 1,600 cloud, IT, and engineering executives conducted by Wakefield Research for Nutanix. Executives who participated in the survey have a minimum title of manager at companies with 500 employees or more across 14 markets: Australia, Brazil, France, Germany, India, Italy, Japan, Mexico, Netherlands, Kingdom of Saudi Arabia, Singapore, Spain, UK, and the United States.
Believe AI is accelerating their adoption of containers
Containers are gaining traction in no small part because of the widespread embrace of AI-enabled applications. Most IT executives (85%) believe that AI is accelerating their organization's adoption of containers in a meaningful way, including 29% who think it's accelerating adoption to a great extent.
Organizations need to modernize their infrastructure to ensure application and workload agility, portability, sovereignty, and cost control. But when business departments operate in isolation and implement AI initiatives on their own without consulting IT, it makes IT's job harder and can lead to inefficiencies and project delays.
These silos also create an opportunity for shadow AI to develop.
Most IT executives (87%) believe that the use of AI tools and agents outside of official oversight creates business risk.
The unauthorized use of AI tools can expose sensitive company information and valuable intellectual property to outside parties, with potential legal consequences for not complying with regulations.
This report explores the many challenges that IT executives face as they navigate the rapid escalation of AI.
Key Findings
Shadow AI is widespread and largely unmanaged.
Believe silos between business units and IT make it difficult to effectively execute technology initiatives
Encounter AI applications or agents implemented by employees in non-IT functions
Believe the use of AI tools and agents outside of official oversight creates business risk
Containers are becoming foundational to application strategy.
Expect the level of application containerization to increase at their company
Think AI is meaningfully accelerating adoption of containers for their organization
Are building new applications in containers
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The Nutanix Survey was conducted by Wakefield Research [wakefieldresearch.com] among 1,600, IT & Engineering Executives, with a minimum seniority of manager, at companies with a minimum of 500 employees across the following markets: Australia, Brazil, France, Germany, India, Italy, Japan, Mexico, Netherlands, Kingdom of Saudi Arabia, Singapore, Spain, United Kingdom, and the United States, with an oversample of 100 Federal U.S. workers, between November 13th and November 23rd, 2025, using an email invitation and an online survey.
Results of any sample are subject to sampling variation. The magnitude of the variation is measurable and is affected by the number of interviews and the level of the percentages expressing the results. For the global interviews conducted in this particular study, the chances are 95 in 100 that a survey result does not vary, plus or minus, by more than 2.38 percentage points; for the United States 4.9, and all remaining countries 9.8, from the result that would be obtained if interviews had been conducted with all persons in the universe represented by the sample.
© 2026 Nutanix, Inc. All rights reserved. Nutanix, the Nutanix logo, and all Nutanix product and service names mentioned herein are registered trademarks or trademarks of Nutanix, Inc. in the United States and other countries. All other brand names mentioned are for identification purposes only and may be the trademarks of their respective holder(s).
Certain information contained in this content may link or refer to, or be based on, studies, publications, surveys, and other data obtained from third‑party sources and Nutanix’s own internal estimates and research. While Nutanix believes such third‑party studies, publications, surveys, and other data are reliable as of the date of publication, they have not been independently verified unless specifically stated, and Nutanix makes no representation or warranty as to the adequacy, fairness, accuracy, or completeness of any information obtained from third‑party sources. Our decision to publish, link to, or reference any third‑party content should not be considered an endorsement of that content. This material is provided for informational purposes only and does not constitute legal, financial, or professional advice.
An AI-Fueled Container Revolution
As enterprises prepare for a future defined by cloud-native architectures, distributed data-centric applications, and Gen AI-driven innovation, they are increasingly adopting containers to bundle their applications' code and libraries.
These bundles enhance data security while bringing agility for tweaking apps.
Looking ahead over the next three years, the vast majority (87%) of executives expect the level of application containerization within their organization to increase.
The migration toward containers is especially strong in India (97%), while among sectors it's most pronounced in finance (89%).
Expect the level of application containerization within their organization to increase over the next three years
Which of the following factors would most likely drive your organization's adoption or increased use of containers in the next 12 months?
Performance
Data security
Developer productivity/time to market
AI readiness/enablement
Portability across environments
Data sovereignty
Cost considerations
The goal of improving speed, reliability, and scalability is the most likely driver for executives to adopt or increase use of containers in the next 12 months, with 47% selecting that as their top objective.
Running resource-intensive AI workloads requires significant IT infrastructure that many companies lack. The AI applications are coming quickly, and often there's more than one in operation. Containers can help by packaging everything an app needs to function in isolated units with orchestration tools such as Kubernetes that reduce setup time and costs.
A strong majority of executives (85%) think that AI is accelerating their organization's adoption of containers in a meaningful way, including 29% who believe it's accelerating adoption to a great extent.
To what extent is AI accelerating your organization's adoption of containers?
To a great extent
To a moderate extent
To some extent
This shift is most obvious in finance and in the public sector, where AI is accelerating adoption of containers to a great extent (39% and 38%, respectively), while healthcare (25%) trails these sectors. Acceleration is also significant among those who anticipate running more than five AI-enabled applications within the next three years (36%).
Simply put, the more AI-enabled applications that IT is juggling, the greater the need for containers. To run an AI model or execute certain training, enterprises need dependencies and software tools. A plethora of software packages must be orchestrated and configured correctly. That infrastructure can then be reproduced reliably, wherever an enterprise desires, by putting it in containers for greater consistency and portability.
Currently, 71% of organizations are running their AI-enabled applications on a mix of traditional apps in virtual machines (VMs) and modern apps in containers on VMrs while 14% are running their AI-enabled apps directly on bare metal servers.
With AI enablement driving container adoption, a strong majority (83%) are building new applications in containers.
When thinking about your organization's use of containers, which best describes your current approach?
Primarily build new apps in containers
A mix of both
Primarily containerize legacy apps
Of respondents are building new applications in containers, driven by AI enablement and the resulting adoption of container technology.
AI Push
The directive to deploy AI applications often comes from the top, with little thought to the infrastructure that will support those applications.
Although IT executives may want to move AI applications on-premises for greater control, they expect little to change in the near term when it comes to applications on containers.
Looking ahead to three years from now, 59% anticipate that their organization will have more than five AI-enabled applications, including 23% who expect to be using more than 10. Types of AI applications or capabilities they expect to use within the next three years but are not currently using include generative AI (58%), agentic AI or autonomous agents (56%), and chatbots or conversational AI (49%).
An organization's decision about where to run its AI applications may impact data security and scalability. The majority (65%) run AI applications on managed service providers, as in a third-party vendor hosting/managing container infrastructure. This demonstrates that AI apps are hybrid by default. Enterprises need consistency to deploy in cloud, on-premises, and at the edge.
Which of the following types of AI applications or capabilities is your organization not currently using but expects to use within the next three years?
Generative AI
Agentic AI or autonomous agents
Chatbot or conversational
Predictive analytics / ML models
Computer vision
Running AI applications on-premises offers enhanced data security and privacy, as well as better regulatory compliance, greater control over performance, and the potential for more customization. Yet if their organization needed to deploy AI workloads on-premises, 82% view their current infrastructure as not fully ready to support this. That's especially true in the healthcare sector (88%).
Within three years, 54% expect their containerized applications to be running on-premises or on a private cloud—a modest bump from 52% currently. A majority (60%) also anticipate that their containerized applications will run via managed service providers in three years, compared with 57% today.
Of organizations report on-premises infrastructure is not fully ready to support AI workloads
Spotlight: Agentic AI on the Horizon
Autonomous software systems that use artificial intelligence can act as versatile digital assistants that learn and adapt over time. This unlocks enormous potential within organizations.
Most IT executives (61%) expect AI agents to enhance customer or employee experiences as part of their company's business strategy.
A majority (58%) also anticipate that AI agents will improve productivity and efficiency.
But some imagine that AI agents can play a deeper, more transformative role. More than half of IT executives see potential for AI agents to create new products, services, or revenue streams (57%).
In what ways do AI agents currently factor into, or could factor into, your organization's business strategy?
Enhancing customer or employee experiences
Improving productivity / efficiency
Creating new products, services, or revenue streams
Transforming business practices and operations
Enabling faster decision making
Spotlight: Importance of Data Sovereignty
Data protection is paramount for IT professionals who are making decisions about infrastructure while complying with local regulations. For the majority (80%), data sovereignty is a high priority or even a must-include when making infrastructure decisions.
Although storing data on-premises can offer more control over applications than keeping data in the public cloud, it can be costly and impractical for some organizations. Many are opting for a hybrid approach.
Nearly the same percentage of enterprises are running their containerized apps on-premises or on a private cloud (52%) as they are on the public cloud (53%).
Why does your organization feel the need to run its infrastructure within a single country (i.e., domestically), whether on premises or through a local cloud region?
Security or data protection concerns
Regulatory / compliance requirements
Customer or stakeholder expectations
Performance / latency reasons
Organizational or national policy alignment
Control and governance
Often, compliance obligations drive organizations to keep data physically within the country where it was collected. More than half (57%) of organizations feel the need to run their infrastructure within a single country (i.e., domestically), whether on-premises or through a local cloud region, largely due to security or data protection concerns.
And when choosing where to deploy containerized applications, meeting compliance and data protection standards plays the greatest role in the decision making; nearly a third (28%) of organizations that run AI-enabled applications in containers cite this as a major factor. While a migration to more on-premises infrastructure could go a long way toward satisfying sovereignty needs, the fast arrival of AI has made this shift unwieldy for many enterprises.
Consider data sovereignty a high priority when making infrastructure decisions
Obstacles in the AI Journey
IT professionals are struggling to control how AI applications are implemented across the enterprise, while also bumping into silos. These barriers get in the way of rolling out and supporting applications.
Of IT executives encounter AI applications or agents being implemented by employees in non-IT functions
Most IT executives (79%) encounter AI applications or agents being implemented by employees in non-IT functions. This means that AI solutions are frequently landing within the enterprise through individual users rather than being spearheaded and sanctioned by the enterprise itself, demonstrating a strong desire among employees to use AI.
Believe use of AI outside of official oversight creates business risk
The unauthorized use of AI tools risks exposing sensitive company information and valuable intellectual property to outside parties, with potential legal consequences for not complying with regulations.
The overwhelming majority of IT executives (82%) think that silos between business units and IT stand in the way.
Shadow AI spreads more easily when business units operate in silos. The overwhelming majority of IT executives (82%) think that silos between business units and IT stand in the way of their organization's overall performance and ability to execute technology initiatives effectively. When different parts of a company aren't talking to each other, there's a heightened need to build a future-ready IT foundation that supports innovation anywhere.
Key Takeaways
Dual Reality
AI apps are being born via default cloud native containers and hybrid.
Hybrid Setup
AI apps require new hardware, but also new software to deliver on performance, governance, multi-tenant and multi-service requirements for a hybrid setup.
Rethinking Infrastructure
AI apps need data and require a rethink of data infrastructure for performance and governance.
Conclusion
Artificial intelligence is being incorporated into workflows at an astounding pace.
Against this backdrop and under pressure to support exploding data needs, executives are searching for the best ways for their companies to secure and quickly deliver data. Enterprises are turning to containers to bundle an application's code and libraries, bringing standardization and automation that helps with data management. Meanwhile, silos prevent coordination between departments and give rise to the use of shadow AI by employees. This shadow AI represents a business risk.
In the age of AI, IT professionals are faced with the dual tasks of meeting business objectives while safeguarding intellectual property and personal data The rapid pace of AI adoption leads to running containers at scale, in production, with the proper infrastructure to support it. Whether on-premises or in the cloud, containers allow for more responsible and secure AI deployment.
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