According to Nutanix, the rapid increase in enterprise AI adoption over the past year has led to a wave of infrastructure modernization as companies race to build and run more efficient applications.
For the eighth year in a row, Nutanix commissioned a global research study to assess the state of cloud adoption, containerization, and GenAI application deployment.
The survey, conducted by Wakefield Research in November 2025, gathered responses from 1,600 cloud, IT, and engineering executives with at least manager-level positions.
Respondents represent organizations with more than 500 employees in Australia, Brazil, France, Germany, India, Italy, Japan, Mexico, the Netherlands, Kingdom of Saudi Arabia, Singapore, Spain, the United Kingdom, and the United States.
Survey results show that containers have become a core component of enterprise application strategies, with 90% of Australian respondents agreeing that AI is accelerating container adoption to improve speed, reliability and scalability.
“It’s clear that Australian organizations are ready to embrace AI, but it requires resilient, reliable and well-managed infrastructure. Containerization has emerged as a fundamental pillar of local AI and application strategies, but broader adoption requires a rethink of the underlying infrastructure,” said Michael Alp, Managing Director, A/NZ at Nutanix.
“Rather than managing two-speed infrastructure stacks, having a common operating environment to manage both containerized and traditional workloads would address key concerns such as shadow IT and data sovereignty,” Alp said.
The results also show that shadow IT poses challenges and security concerns for AI. 72% of respondents have encountered an AI application or agent implemented by an employee outside of the IT department.
Additionally, 92% of Australian leaders believe that misuse of AI poses risks, including the loss of sensitive data and intellectual property. This highlights the need for close collaboration between IT teams and business stakeholders to keep AI deployments secure, compliant, and aligned with organizational goals.
Additionally, organizational silos create new AI risks. While the adoption of AI is driving innovation, it is also creating operational challenges. 84% of Australian respondents believe that silos between business units and IT make it difficult to effectively execute technology initiatives, delay implementation timelines, and increase complexity.
Additionally, agents unlock huge potential for your organization. Most Australian IT executives (70%) also expect AI agents to improve productivity and efficiency. Three in five (62%) expect AI agents to improve the customer or employee experience.
Additionally, some believe AI agents could play a deeper role, with 58% believing AI agents could create new products, services, or revenue streams.
The findings also show that data sovereignty is non-negotiable. For 89% of Australian respondents, data sovereignty is a top priority when making infrastructure decisions, including where to utilize containers. This compares to 80% worldwide.
More than half (60%) of Australian leaders feel the need to run their infrastructure domestically, either on-premises or through a local cloud region, primarily due to security or data protection concerns.
Additionally, containers are the foundation of modern applications, with AI being a key driver. Organizations are turning to containers to support AI-enabled workloads and modern application development. Among respondents, 85% expect the use of containers in applications to increase over the next three years, and 66% say they are already building new and legacy applications with containers.
Nine out of 10 respondents believe that AI is accelerating container adoption, highlighting why enterprises need to evolve their infrastructure strategies to handle containerized workloads.
Additionally, the directive to deploy AI applications comes from the top, but the infrastructure is not fully prepared to support it. Almost half of respondents (48%) expect their organization to implement five or more AI-enabled applications in the next three years.
However, if organizations need to deploy AI workloads on-premises, 87% believe their current infrastructure is not fully prepared to support this.
