Building, deploying and scaling enterprise AI applications require organizations to overcome significant hurdles, including high costs, insufficient infrastructure and skill gaps. Addressing these challenges demands innovative solutions that prioritize simplicity and user experience, according to Mandy Dhaliwal, chief marketing officer of Nutanix Inc.

[Artificial intelligence] is a C-suite and boardroom priority,” Dhaliwal told theCUBE in an interview. “Fifty-nine percent of companies … believe it is going to change the way they operate fundamentally … almost half … have already got a workforce productivity plan in place for leveraging AI.”

Dhaliwal and other Nutanix leaders spoke with theCUBE Research’s Dave Vellante at The AI-Ready Platform: Nutanix Simplifies Enterprise AI event, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. Discussion centered on innovative strategies to overcome AI adoption challenges and drive enterprise AI applications across hybrid and multicloud environments. (* Disclosure below.)

Here are three key insights you may have missed from theCUBE’s coverage:

1. Hybrid cloud and full-stack solutions simplify adopting enterprise AI applications.

Organizations seeking enterprise AI applications face challenges in transforming infrastructure, scaling systems and securing deployments, according to Justin Boitano, vice president of enterprise AI at Nvidia Corp. Nutanix and Nvidia address these needs with hybrid cloud solutions and full-stack accelerated computing designed to meet the demands of generative and agentic AI.

Nvidia’s Justin Boitano and Nutanix’s Tarkan Maner talk with theCUBE about the Nutanix and Nvidia partnership and the urgency for enterprises to embrace AI as a catalyst for growth and efficiency.

“What we’re seeing is the fundamental shifts across three vectors happening simultaneously,” Boitano told theCUBE in an interview segment during the event. “First, the world needs to move away from traditional computing into full-stack accelerated computing. The second thing we see is as people go to full stack accelerated computing, it requires reinvention of the entire infrastructure. All of your software across your state has to change, and all of this has to be done to power this new world of generative AI. Finally, the third vector that we see is agentic AI.”

Nutanix’s hybrid multicloud architecture, powered by Nvidia’s innovative AI models, offers companies a secure and flexible platform to deploy custom enterprise AI applications, according to Boitano. These applications address a range of use cases, from customer support automation to advanced data retrieval, while enabling secure on-premises deployment for proprietary information within enterprise AI applications.

“Most [enterprises] want to keep their proprietary information confidential, and they want to run it in a protected way on their network,” Boitano said. “But they want to harness all the automation benefits and this new level of intelligence to augment their workforce and drive better efficiency and productivity across the board.”

Looking to the future, Nutanix and Nvidia are poised to lead advancements in agentic AI — software entities designed to handle repetitive tasks autonomously. With Nvidia’s AI blueprints offering best-practice models for common scenarios, organizations can expect faster adoption of enterprise AI applications and enhanced productivity, according to Tarkan Maner (pictured), chief commercial officer at Nutanix.

“We announced originally a more data-centric approach to this,” he said during the interview with Boitano. “Now, we’re taking this to [the] cloud. Our goal is to take this to the next level, basically giving the customer a complete open platform where they can run their AI workloads across data centers at the edge and in the cloud with partnerships with [Amazon Web Services], Google Cloud and [Microsoft] Azure. They’re all part of this new enigma, new go-to-market model for us.”

Here’s the complete interview with Justin Boitano and Tarkan Maner:

2. Kubernetes advancements streamline AI workload management.

At KubeCon + CloudNativeCon NA, Nutanix emphasized its commitment to simplifying Kubernetes management to accelerate the adoption of enterprise AI applications. Recognizing Kubernetes as essential for modern workloads, Nutanix focuses on streamlining its complexity, according to Toni Knaup, chief executive and co-founder at D2iQ Inc.

Nutanix’s Luke Congdon talks with theCUBE about the key role that Nutanix Enterprise AI plays in simplifying infrastructure management.

“There’s lots of observability tools, and we want to a service mesh and all these other things. With AI added to it, that’s driving even more complexity,” he told theCUBE Research’s Savannah Peterson in a pre-event interview. “They run on different infrastructures, so it’s something we’re focused on. What we do is … embrace Kubernetes application programming interface model early on to run everything up and down the stack, declarative APIs for everything, cluster APIs so that people can deploy their Kubernetes clusters consistently across any infrastructure, and just building a lot of automation in general to make it easy to use.”

Nutanix’s Kubernetes strategy builds on these principles, using automation and partnerships to simplify containerized workloads across diverse infrastructures, according to Luke Congdon, senior director of product management at Nutanix. By integrating partnerships with Nvidia and Hugging Face Inc., Nutanix ensures enterprises can deploy AI workloads quickly, reducing complexity and accelerating productivity.

“Partnerships, I think, are the way to do it,” he told theCUBE in an interview segment that aired at KubeCon. “Even on the NAI announcement, we partnered with Hugging Face for access to their hub because they’ve got all the models in the world. We’ve also partnered with Nvidia, and we’ve been doing that for years both on the [graphics processing unit] side for virtual desktop, as well for their AI for Enterprise suite and their NIMs products.”

Here’s theCUBE’s complete video interview with Luke Congdon:

3. Multicloud platforms drive scalable AI and machine learning.

Nutanix’s multicloud platform enables enterprise AI applications deployment and management across the edge, cloud, and on-premises, according to Bob Parker, senior VP of industry, software and services research at International Data Corp. By offering predictable pricing and robust infrastructure, Nutanix provides enterprises with the flexibility needed to scale AI workloads efficiently.

IDC’s Bob Parker, Nutanix’s Thomas Cornely and Nutanix’s Mandy Dhaliwal talk with theCUBE about how Nutanix is meeting the growing AI demand and developing an effective enterprise AI strategy.

“The average company has about 37 proof of concepts as of the midpoint this year, but only five of those go to production. Then only about two-thirds of those are considered successful,” Parker said in an interview segment during the Nutanix AI-Ready event. “We’re moving to a pivot where people are looking at multiple use case strategies. It is multi-model … and it’s multicloud, as I need to deploy it at the edge and in the cloud and in the data center. It’s very early days, but we are seeing … this emergence of an AI pivot towards a much more comprehensive enterprise AI strategy.”

By delivering a unified platform, Nutanix equips enterprises with the tools to manage enterprise AI applications and data across diverse environments, according to Thomas Cornely (center), senior VP of product management at Nutanix. This approach focuses on simplicity, enabling organizations to scale AI workloads effectively while maintaining control over their data and infrastructure.

“This focus on simplicity, focus on user experience, focus on data and controlling your data, focus on giving you a platform to simply run your applications, that to us were just a natural extension,” Cornely told theCUBE during the Nutanix event. “If you’re going to … need a platform that allows customers to go and run all their applications and manage that data anywhere, well, you have to do it for their AI-based applications and data … there’s a big need for enterprise customers to get the tooling to stand up those infrastructure platforms to support those new applications.”

Here’s the complete video interview with Bob Parker, Thomas Cornely and Mandy Dhaliwal:

To watch more of theCUBE’s coverage of The AI-Ready Platform: Nutanix Simplifies Enterprise AI event, here’s our complete event video playlist:

(* Disclosure: TheCUBE is a paid media partner for The AI-Ready Platform: Nutanix Simplifies Enterprise AI event. Neither Nutanix Inc., the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

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