The Data Center Frontier Show

Artificial intelligence will continue to transform how data centers are designed, built, and operated, placing new demands on energy systems, infrastructure, and reliability. As AI workloads grow more intensive and always‑on, meeting these challenges will require a coordinated, systems‑level approach. 

In this episode, Patrick Hughes, SVP of Technical and Industry Affairs at the National Electrical Manufacturers Association (NEMA) will explore the AI Data Center Energy Performance Framework, developed in collaboration with ASHRAE and Pacific Northwest National Laboratory. The Framework provides practical, expert‑driven guidance to help owners, operators, engineers, and policymakers navigate the evolving AI landscape. 

He will provide an overview of why the Framework was created and how it is intended to be used. With thousands of data centers already operating—and many more planned—AI will drive higher load densities and increase pressure on both facilities and the grid. The Framework offers a shared foundation to align energy performance, reliability, and resilience across the full lifecycle of a data center. 

The conversation will also highlight NEMA’s role in ensuring electrical systems are fully integrated into data center design. Power distribution, safety, and infrastructure will need to work seamlessly with cooling and thermal management to avoid operational risks and support long‑term performance. 

A key theme of this Framework is collaboration. By bringing together NEMA’s leadership in electrical infrastructure, ASHRAE’s expertise in building systems, and PNNL’s energy research capabilities, the Framework will bridge traditional silos and promote a more integrated approach. 

We will also discuss how the Framework supports both new builds and existing facilities, helping organizations modernize infrastructure to meet AI demands. As a living, evolving resource, it will adapt alongside rapid changes in technology and energy needs. He’ll also explore what it means for communities and policymakers as data center growth accelerates—offering a path to balance innovation with reliability, efficiency, and long‑term infrastructure planning.

Hyperscale AI campuses command the headlines, but the next major wave of AI adoption may play out across enterprise data centers measured in megawatts rather than hundreds of megawatts.

In this episode of the Data Center Frontier Show, DCF Editor in Chief Matt Vincent sits down with Kirk Killian, President of Partners National Mission Critical Facilities, to examine how Fortune 1000 and Global 2000 organizations are preparing for AI—and why their infrastructure priorities differ sharply from those of hyperscalers.

Killian argues that while enterprises are comfortable outsourcing AI training, the rise of AI inference could drive sensitive workloads back toward on-premises environments and private colocation deployments, where latency, security, compliance, and operational control become paramount. He also explains why enterprise customers continue to prioritize reliability and flexibility over sheer scale, how cabinet densities are evolving, why liquid cooling optionality matters even when it's not immediately needed, and what developers can do to better serve this often-overlooked market.

The conversation also explores the future of hybrid cloud, the economics of AI infrastructure, emerging enterprise site selection trends, and why “cloud plus controlled” may become the dominant architecture for enterprise AI.

For anyone focused on the next phase of AI infrastructure—not just the largest campuses, but the environments where AI will be embedded into everyday business operations—this discussion offers an important and frequently overlooked perspective.

As AI infrastructure scales from megawatts to gigawatts, liquid cooling is rapidly becoming a foundational technology rather than a specialized option.

In this episode of the Data Center Frontier Show podcast, recorded at Motivair's headquarters and manufacturing facility in Buffalo, New York, DCF Editor in Chief Matt Vincent sits down with Motivair CEO Rich Whitmore to discuss the evolution of liquid cooling from its roots in high-performance computing to its central role in today's AI data centers.

Whitmore explains how Motivair's decade-plus experience supporting supercomputing environments helped position the company for the current AI boom, which he describes as the commercialization of traditional HPC at unprecedented scale. The conversation explores how liquid cooling products are developed years ahead of silicon roadmaps, why manufacturing discipline and testing standards have become competitive differentiators, and how global production capacity is increasingly essential as AI deployments accelerate worldwide.

The discussion also examines one of the industry's emerging technical debates: whether ever-larger "facility-scale" coolant distribution units are the best answer for AI infrastructure. Whitmore offers a unique perspective on the realities of thermal management, noting that while AI workloads can change almost instantaneously, mechanical cooling systems must still operate within the physical constraints of pumps, valves, and fluid dynamics.

The interview was recorded during a Schneider Electric global media event that included a tour of Motivair's Buffalo manufacturing operations and the nearby 750 MW TeraWulf Lake Mariner AI campus. There, Motivair liquid cooling technologies—including CDUs, in-rack manifolds, and ChilledDoor rear-door heat exchangers—are helping support one of North America's most ambitious AI infrastructure developments.

As Whitmore explains, the question facing the industry is no longer whether liquid cooling will become mainstream. That transition is already underway. The challenge now is executing at scale—and building the manufacturing, supply chain, and engineering capabilities required to support the next generation of AI infrastructure.

Water has long been an overlooked piece of data center infrastructure, but that is rapidly changing as AI development accelerates across the industry.

In this episode of the Data Center Frontier Show podcast, DCF Editor in Chief Matt Vincent sits down with Anurag Bajpayee, co-founder and executive chairman of Gradiant, to discuss why water is increasingly emerging alongside power as one of the most important constraints facing future data center development.

Bajpayee explains how hyperscale operators are beginning to view water availability, reuse, discharge management, and community acceptance as strategic business issues rather than simply sustainability concerns.

He also discusses Gradiant's end-to-end approach to industrial water treatment, including advanced recycling technologies, AI-driven operational optimization, and the company's vision for helping data centers become less dependent on municipal water supplies.

Among the topics touched on:

• Why operator interest in water strategy has surged over the past 12 to 24 months

• How water availability is becoming a siting, permitting, and business continuity issue for AI campuses

• The concept of "controlling your water destiny"

• Turning wastewater into a resource through recycling and reuse

• How AI can optimize water treatment operations in real time

• What data centers can learn from the semiconductor industry's evolution in water management

• The water implications of direct liquid cooling and next-generation AI infrastructure

• Why water stewardship is increasingly becoming a business strategy rather than solely an environmental initiative

As AI infrastructure scales to unprecedented levels, the industry's resource challenges are expanding beyond power alone. This conversation offers a timely look at why water is becoming a critical component of data center planning, operations, and long-term growth.

Listen now to hear how Gradiant views the future of water infrastructure in the AI era and why operators are increasingly seeking greater control over one of their most essential resources.

Recorded live at Data Center World 2026, Data Center Frontier Editor in Chief Matt Vincent sits down with Phillip Koblence, COO of NYI and co-founder of Nomad Futurist, for the latest installment of Nomads at the Frontier.

The conversation explores the accelerating realities of AI infrastructure buildouts, the industry’s growing focus on community engagement, workforce shortages, and the shift toward inference-driven deployments following NVIDIA GTC 2026.

Koblence discusses why major interconnection hubs and edge-adjacent urban facilities may become increasingly important in the inference era, the operational realities of deploying AI infrastructure in legacy carrier hotels like 60 Hudson Street, and why the industry can no longer remain invisible to the communities where it builds.

Additional topics include:

The continuing surge in digital infrastructure demand

Why conference attendance reflects sustained industry expansion

Power constraints and energy storage discussions emerging at Data Center World

AI factories and the evolving economic role of data centers

Workforce shortages across engineering and skilled trades

Nomad Futurist’s workforce development initiatives with Infrastructure Masons and I Am The Armed Forces

The growing complexity and diversity of the data center ecosystem

“Every element of everything within the data center has a full sub-vertical industry associated with it,” Koblence says during the discussion. “People would be surprised how large of an ecosystem is involved in creating the digital economy that exists today.”

Listen now for a candid, fast-moving conversation on the state of AI infrastructure and the future of digital infrastructure development.