AI adoption is accelerating the adoption of containers within enterprises. But that same push is also exposing governance gaps, infrastructure shortfalls and rising concerns around data sovereignty.
Those insights come courtesy of cloud software vendor and VMware rival Nutanix in its latest Enterprise Cloud Index report. The eighth annual survey, released in early March, was conducted in November 2025 by Wakefield Research and included 1,600 cloud, IT and engineering executives at organizations with 500 or more employees across 15 countries.
Organizations are reworking infrastructure and application strategies as they prepare to support a growing number of AI-enabled workloads, Nutanix found. Nearly 9 in 10 respondents said AI is speeding their adoption of containers. Roughly the same proportion expect container use for applications to increase over the next three years.
The shift reflects mounting enterprise enthusiasm for agentic AI, according to Nutanix. Nearly two-thirds of respondents expect AI agents to improve customer or employee experiences, while 58% expect productivity and efficiency gains. Another 57% said agents could help create new products, services or revenue streams.
For channel partners, the trend creates opportunities that go beyond AI pilots and into the harder work of modernization: helping customers build cloud-native foundations, address governance and security issues, and identify where AI infrastructure and data can legally and operationally reside.
“The findings indicate organizations need enterprise-grade security, resilience and portability as AI workloads can run anywhere,” said Lee Caswell, SVP of product and solutions marketing at Nutanix.
He added that organizations would benefit from “a common operating environment for virtual machines and containers” to help IT teams deploy AI across hybrid environments.
Data points for partners
One of the more notable findings for partners is the degree to which sovereignty and location requirements are shaping infrastructure decisions.
Four in 5 respondents view data sovereignty as a high priority when deciding where to run infrastructure, including containerized environments. More than half said they feel the need to keep infrastructure within a single country, whether on premises or in a local cloud region, largely due to security and data protection concerns.
The findings have implications for solution providers, MSPs and systems integrators helping customers design hybrid and multicloud environments. Enterprises may want the flexibility of cloud-native AI development, but they also face pressure to keep sensitive data, models and workloads in-country to meet compliance, customer and internal governance mandates. That tension stands to create demand for partners who can help customers balance portability and sovereignty.
But partners need to move quickly.
Nutanix noted that AI is arriving faster than enterprise infrastructure can support it, an observation that has frequently appeared in vendor and independent research over the past year. While 59% of respondents expect their organizations to have more than five AI-enabled applications within three years, 82% said their current infrastructure is not fully ready to support on-premises AI deployments.
“AI didn’t wait for your enterprise to be ready,” said Dan Ciruli, VP of cloud native at Nutanix. That’s creating problems that partners will need to solve.
As ungoverned AI adoption moves forward, data silos form within business units — outside of IT’s oversight. Indeed, 79% of respondents in the Nutanix survey reported “finding AI apps built completely outside IT,” Ciruli said.
More than 4 in 5 respondents said these silos make executing tech initiatives more difficult, slowing deployment timelines and increasing complexity. “That’s shadow AI, and it’s growing,” Ciruli said.
It threatens more than internal operations. Roughly 9 in 10 respondents told Nutanix shadow AI “creates real business risk,” Ciruli said. Unauthorized AI use is ungoverned, heightening the chances that sensitive data and intellectual property will be exposed.
Providing AI governance, security and implementation guidance should prove just as important to partners as selling infrastructure. Enterprises are under pressure from leadership to move quickly on AI, but many are doing so without the considerations needed to scale it safely.
