The artificial intelligence revolution is reshaping IT at every level, from infrastructure to operating models. On the latter, AI is forcing a business model reset, as enterprises grapple with the pressure to manage costs, minimize downtime and rethink where workloads live — whether at the edge, in private cloud or on-premises.

Future Tech’s Michael Watkinson discusses the new AI business model with theCUBE.

VMware’s strategy, for instance, is tightly linked to this shift. The platform’s latest release, VCF 9, is designed to streamline operations and give organizations flexibility in how they deploy, according to Michael Watkinson (pictured), chief revenue officer of Future Tech Enterprise Inc.

“It’s about the transformation and not the transaction,” he said. “Our customers, too, they’ve invested in VCF over time. They’ve implemented NSX and those things are hard to extract for … a large franchise parts of a business, but there are thousands of smaller networks out there that need to make decisions still. We’re really trying to put ourselves in the middle of those discussions on how you categorize the workloads and where they’re going.”

Watkinson spoke with theCUBE’s John Furrier and Rebecca Knight at VMware Explore, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how VMware and partners such as Future Tech help enterprises navigate AI and cloud transformation, with success hinging on long-term planning, governance and ecosystem collaboration. (* Disclosure below.)

Future Tech’s strategic role in driving the new AI cloud business model

Future Tech is one of VMware’s many strategic partners, focusing heavily on the federal sector and financial services industries. With deep roots in Dell Technologies Inc. and Nvidia Corp.’s ecosystems, the company is positioned to help clients operationalize large enterprise agreements and move beyond transactional IT buying. For Future Tech, the goal of today’s AI business model should be transformation, not just technology procurement. This includes building GPU-powered clusters for AI, guiding customers through chargeback and cost-allocation models and preparing for the dense compute and storage needs of tomorrow.

“We put ourselves right in those conversations in terms of how we operationalize these ELAs and this spend,” Watkinson said. “Operationalizing that involves doing the drawdowns and the chargebacks, just as much as creating some optionality.”

Beyond hardware, the people side of digital transformation looms large. As enterprises accelerate AI adoption, skills gaps and governance challenges are emerging. This has led to the emergence of “shadow AI,” where teams experiment independently with new tools and models outside IT oversight, Watkinson added.

“Shadow AI is happening everywhere, and how do we bring that to the surface?” he said. “When we do that, we start to see patterns. We start to see what’s common, repeatable and scalable. And in doing that, we can start to create everything in a box and the right tools to do the jobs.”

Future Tech’s approach has been to surface these experiments, identify repeatable patterns and formalize them into enterprise-ready frameworks. A notable example: it was the first company to transact an Nvidia enterprise license agreement, which helped customers consolidate AI experimentation under a governed model while still fostering innovation.

“It goes back to trying to understand what those workloads are and where the placement should be, but it’s that journey of understanding the refresh,” Watkinson said. “Many of our customers struggle with asset management in general and what those refresh milestones are that we’re trying to get ahead of that.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of VMware Explore:

(* Disclosure: Future Tech Enterprise Inc. sponsored this segment of theCUBE. Neither Future Tech nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE