Nutanix sharpens its AI strategy with bold innovations aimed at redefining data infrastructure in the hybrid multicloud era.
At its annual .NEXT 2025 conference held in Washington, D.C., Nutanix made it clear that its vision for the future of enterprise infrastructure is inextricably tied to artificial intelligence.
While the event brought together thousands of global IT leaders and cloud architects, the most transformative discussions centered around the company’s latest advancements in Nutanix Enterprise AI (NAI)—a comprehensive suite of tools and capabilities designed to power next-generation, AI-ready infrastructure.
Pivot Toward Enterprise AI
With enterprises demanding more intelligent, adaptive infrastructure to handle evolving workloads, Nutanix is stepping up with a clear message: hybrid multicloud must be AI-optimized from the ground up.
The NAI initiative aims to help organizations securely manage and scale their AI and machine learning workloads across data centers and public clouds, without the complexity traditionally associated with such deployments.
At the heart of this effort is Nutanix’s GPT-in-a-Box platform—a ready-made solution that delivers GPU acceleration, integrated MLOps pipelines, and AI governance tools within a single, simplified interface.
This solution is purpose-built to bring generative AI closer to enterprise data while maintaining control, compliance, and performance.
Key Enhancements to Nutanix Enterprise AI
During .NEXT 2025, Nutanix unveiled several new features that enhance the utility and reach of its Enterprise AI platform:
Expanded External Storage Support
Enterprises can now connect external storage arrays to Nutanix clusters. This unlocks more flexibility for AI model training, which typically involves massive datasets stored outside the core HCI environment.
Kubernetes-Native AI Workload Management
Nutanix introduced deeper integration with Kubernetes, allowing AI workloads to be deployed and managed seamlessly within containerized environments—ideal for scaling inference and training models in production.
Integrated AI Observability Tools
Nutanix now offers built-in observability for AI pipelines, enabling real-time monitoring of GPU utilization, data movement, and workload performance. These insights are essential for optimizing large language model (LLM) training and inference cycles.
Enhanced Security and Governance for AI Workflows
With AI models increasingly intertwined with sensitive business logic and customer data, Nutanix has embedded zero-trust controls and auditing capabilities into the AI stack to ensure that model usage aligns with enterprise policies.
Nutanix + Cohesity
Further boosting its AI credentials, Nutanix announced a strategic integration with Cohesity to bring natural language access to backup and recovery workflows.
Cohesity’s conversational AI assistant, Gaia, now works natively with Nutanix GPT-in-a-Box, allowing IT teams to interact with their data protection infrastructure using simple queries like
“show me the latest backup job status” or “restore the last 24 hours of database logs.”
This move underscores Nutanix’s ambition to turn every part of the IT stack—from infrastructure to data services—into a smart, conversational, AI-augmented experience.
The Bigger Picture
While much of the industry is still grappling with how to operationalize AI in enterprise settings, Nutanix is offering a blueprint: simplify, secure, and scale AI infrastructure using a platform-first approach.
By weaving AI deeply into its HCI and cloud management offerings, Nutanix is positioning itself not just as a cloud infrastructure vendor—but as a key enabler of enterprise intelligence.
For IT leaders exploring how to turn their hybrid cloud investments into AI-ready platforms, Nutanix’s Enterprise AI vision offers a compelling, practical pathway.
