UPDATED 13:00 EST / NOVEMBER 12 2024

TheCUBE talks with industry experts about about the importance of developing an enterprise AI strategy that considers cost and data infrastructure. AI

Navigating the AI scramble: A roadmap to effective enterprise AI strategy

Companies now have to look long term when it comes to the ongoing artificial intelligence trend, with a focus on developing an overarching enterprise AI strategy.

Nutanix Inc. aims to support customers’ entire AI infrastructure with software that allows them to deploy AI models in a hybrid environment, with an eye toward machine learning’s game-changing impact.

“AI is a C-suite and boardroom priority,” said Mandy Dhaliwal (pictured, right), chief marketing officer of Nutanix. “Fifty-nine percent of companies that we talked to in our recent research believe it is going to change the way they operate fundamentally. There’s 9% of customers saying that agility is going to be a concern and something that they’re looking forward to from AI. Also, most interestingly, over 49%, so almost half of the folks that we’ve talked to recently, say they’ve already got a workforce productivity plan in place leveraging AI.”

Dhaliwal, along with Thomas Cornely (middle), senior vice president of product management at Nutanix, and Bob Parker (left), senior vice president of industry, software and services research at International Data Corp., 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. They discussed how Nutanix is meeting the growing AI demand and developing an effective enterprise AI strategy. (* Disclosure below.)

Managing costs with enterprise AI strategy

Companies are in the middle of what Parker terms an “AI scramble.” He identifies four primary reasons for failing AI strategies: excessive costs, inadequate data infrastructure, a lack of coordination between IT and business strategy, and a skill gap when it comes to employees who can manage AI software.

“The average company has about 37 proof of concepts as of the midpoint this year, but only five of those go to production. And then only about two-thirds of those are considered successful,” Parker said. “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.”

To answer this issue, Nutanix has created Nutanix Enterprise AI, software that can be deployed on any Kubernetes platform. This cost-efficient platform allows companies to bring in AI-ready infrastructure, such as Nvidia or Hugging Face models, according to Cornely.

“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,” he said. “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.”

Another feature Nutanix offers is its predictable pricing, since the customer is consuming software instead of a service. The company’s platform also allows organizations to capitalize on the hybrid AI trend by running the software on the edge or in the cloud. Part of Nutanix’s strategy is using their own software, according to Dhaliwal. 

“We drink our own champagne around here,” she said. “We have a support GPT, we have a sales GPT, we have an engineering GPT, and the use cases are all around speed to response and accuracy for customer-facing roles, business process alignment around the revenue operations side, automation of repeatable tasks from an engineering perspective, i e, creation of unit tests.”

Nutanix is enhancing its capabilities through technology to become a valuable resource in the industry. While the company is a technology provider, it also positions itself as a trusted advisor to its customers, Dhaliwal added.

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE Research’s coverage of The AI-Ready Platform: Nutanix Simplifies Enterprise AI event:

Watch the entire episode below:

(* 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.)

Photo: SiliconANGLE

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