From Migration to AI: How Nutanix and Microsoft Help Enterprises Run What’s Next, Anywhere
AI is creating new urgency to modernize infrastructure. Enterprises still need to run the applications and data that keep the business moving.
At Microsoft Ignite 2026, Nutanix and Microsoft showcase a simple path from migration to modernization to production AI. Creating a unified operating model across the datacenter and Azure, so organizations can move workloads, put data where it makes the most sense, and introduce AI without creating another isolated stack.
AI projects bring new decisions about governance, data access, model choice, cost control, and workload placement. While legacy workloads, applications, and databases remain essential to daily operations. Most organizations cannot pause the business to rebuild their infrastructure around a single new technology.
They need a way to modernize in steps while maintaining the flexibility to adapt to meet the future needs of their business.
Escape VMware Disruption
VMware disruption is pushing more enterprises to consider alternative infrastructure delivery models. Gartner’s 2026 Strategic Roadmap for VMware Modernization forecasts that by 2029, 55% of enterprises will have migrated 100% of their workloads from VMware to alternative solutions.¹
For organizations evaluating the future of their Azure VMware Solution (AVS) or planning a move from VMware, Nutanix Cloud Clusters (NC2) on Azure provides a path to run the Nutanix software stack on Azure BareMetal Infrastructure.
That path gives teams a familiar operating model across the datacenter and Azure. They can move workloads while preserving existing application architectures, operational practices, and familiar skills. Nutanix Move can help teams automate their migrations from VMware while minimizing downtime.
NC2 on Azure also gives organizations more flexibility in how they can make the most of their Azure investments. For eligible customers, Nutanix software purchased through the Azure Marketplace can contribute to Microsoft Azure Consumption Commitment (MACC) drawdown.
A consistent operating model gives teams a place to run workloads today while creating a foundation for the next phase of modernization.
Create a Foundation for AI
AI applications depend on the business applications that provide context, the databases that hold operational data, and the controls that determine where information can be accessed and processed. NC2 on Azure, Nutanix Central, and Nutanix Database Service (NDB) can help connect those pieces across environments. Teams can use a unified Nutanix operating model across the datacenter and Azure while flexibly choosing workload placement based on business, technical, cost, and regulatory requirements.
Keep databases close to applications and data while managing them consistently across on-premises environments and NC2 on Azure. NDB lets teams provision, operate, protect, and scale database workloads through the same workflows in each location, including when AI use cases depend on information that cannot simply move to the public cloud. Leveraging Nutanix HCI, data locality gives each NDB-managed database VM local access to its data on the node where it runs, delivering lower latency and higher throughput.
With a foundation that supports modernization, organizations can quickly move workloads to NC2 on Azure, keep a sensitive database on-premises, or distribute workloads across environments without changing the operating model each time.
Run AI Securely, and at Scale
As organizations move AI into production, the risks can begin to outpace the returns. Gartner’s IT Symposium keynote found that 86% of CIOs say AI risk is growing faster than AI value, with risk increasing 4 times faster on average. ² At the same time, adopting Agentic AI introduces new challenges, including rising token costs, governance and data privacy requirements, and increasing operational complexity.
Nutanix helps organizations streamline the move from AI experimentation to production with Nutanix Enterprise AI (NAI), a unified, enterprise-grade platform for deploying, managing, and governing AI workloads across hybrid environments. NAI includes Nutanix Agent Gateway and Nutanix Private Inference, helping organizations streamline AI development, enforce centralized governance over agents and models, and gain visibility into token usage and costs.
With Nutanix Agent Gateway, organizations gain centralized token observability across model providers, helping IT and platform teams monitor usage, attribute costs, and identify runaway consumption with token-based rate limiting. It also provides control over how AI agents access enterprise tools and private data sources through MCP servers, with strict access control and audit logging to mitigate enterprise risk.
As organizations seek greater control over sensitive data and AI costs, Nutanix Private Inference delivers a self-hosted inference platform that allows teams to run self-hosted models with efficient inference, predictable costs, and data control. A curated catalog of pre-validated models from Hugging Face and NVIDIA NIM simplifies model deployment, while enterprise-grade authentication and user management policies help protect access to sensitive AI workloads.
Together, Nutanix Agent Gateway and Nutanix Private Inference help power Nutanix Agentic AI, a full-stack platform that helps organizations operate agentic AI at scale with security, governance, and cost control.
Modernize the Surrounding Estate
AI initiatives depend on the broader environment around them. Users need secure access to applications. Databases need to stay available. And existing workloads need to keep running while new services are introduced.
Keep desktops on-premises when data sovereignty or performance requirements demand it while managing them through Azure’s cloud control plane. Azure Virtual Desktop (AVD) Hybrid combines Microsoft’s AVD control plane with Nutanix AHV, allowing organizations to run session hosts in their datacenter while preserving a consistent Azure identity, policy, and management experience.
This can help organizations address data sovereignty, compliance, performance, and cost requirements while preserving control over workload placement. It also gives organizations evaluating the future of traditional virtual desktop infrastructure a way to adopt a Microsoft-native management experience without moving every desktop workload to the cloud.
Many organizations already have, or are investing in, NVIDIA vGPU-enabled infrastructure for demanding desktop workloads. Those same resources can support AI initiatives, extending the value of existing infrastructure beyond productivity workloads. A common Nutanix platform can help organizations avoid building separate silos for virtual desktops and AI.
Service providers can apply the same model to deliver hybrid desktop services and AI-enabled offerings from a common infrastructure platform. That can improve utilization while creating room for new services and opportunities.
Organizations can modernize databases, move workloads when there is a clear benefit, and keep other systems where they perform best. Modernization becomes a flexible sequence of decisions and moves that make sense for the business, rather than one complex, disruptive project.
Set Yourself Up for Enterprise AI Success
The organizations best positioned for AI will be able to run applications, data, and models wherever business requirements demand.
Whether your next step is moving a VMware workload from AVS to NC2 on Azure, standardizing database operations with NDB, modernizing desktop delivery with AVD Hybrid, or giving developers governed access to AI services through NAI, Nutanix can help.
At Microsoft Ignite, visit Nutanix booth 6179 to see how Nutanix and Microsoft are helping organizations connect migration, hybrid cloud operations, and AI on a flexible, resilient foundation. Explore our demos and in-booth theater sessions to see how Nutanix can help you accelerate your migrations, support a foundation for AI, run AI securely, and modernize at the pace business demands.
The path to enterprise AI doesn’t have to mean starting over or rebuilding everything. It can start with creating enough consistency to move, modernize, and run what matters wherever the business needs it.
References
¹ Gartner, 2026 Strategic Roadmap for VMware Modernization, Julia Palmer, et. al, 07 April 2026.
² Gartner, Gartner IT Symposium/Xpo™ Keynote, 19 October 2026.
GARTNER is a trademark of Gartner, Inc. and/or its affiliates.
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