The Data Center Frontier Show

The AI infrastructure race is largely about getting more computing into data centers faster. But increasingly, operators also need a plan for getting yesterday’s hardware back out while it still has value.

In this episode of the Data Center Frontier Show, recorded live at the third annual DCF Trends Summit in Reston, Virginia, DCF Contributing Editor Doug Black speaks with Josh Humm, Data Center Solutions Manager at Dynamic Lifecycle Innovations, about how accelerated AI hardware cycles are changing IT asset disposition, or ITAD.

Humm says traditional enterprise infrastructure might remain in service for three to five years. Newer GPU systems, by comparison, can face refresh cycles of just 18 to 24 months. That compressed timeline is colliding with another AI-era reality: the equipment itself is getting heavier, more specialized and more difficult to remove.

AI systems can include liquid-cooling manifolds, proprietary configurations and units weighing 5,000 to 6,000 pounds, requiring specialized rigging and decommissioning procedures. At the same time, valuable processors, memory, storage and networking components can depreciate quickly once equipment is taken offline.

“The faster we can get the materials out of your building, the more it’s worth, the more we can return to your program,” Humm says.

The result, he argues, is that ITAD should become part of lifecycle planning rather than something operators begin thinking about only when hardware reaches end of life.

The conversation examines how operators can design decommissioning workflows into facility operations, maintain defensible chains of custody, securely destroy data and determine whether retired equipment should be resold whole, harvested for components or recycled.

Humm also discusses the risks created by vendor handoffs across onsite decommissioning, transportation, processing, remarketing and recycling. He recommends scrutinizing providers for data-security and environmental certifications, downstream transparency and the ability to scale as AI refresh projects grow larger.

The economics can be substantial.

Humm describes a recent project involving an approximately 8- to 10-MW enterprise data center in Colorado whose owner was migrating from on-premises infrastructure to the cloud. Dynamic removed racks and equipment, wiped hard drives onsite and shredded drives that could not be successfully sanitized.

After roughly three months, Humm says the project returned more than $17 million net to the customer — about $15 million more than expected.

That outcome highlights a larger issue emerging around AI infrastructure: decommissioning is not necessarily just a disposal cost. In a strong secondary market for memory, processors and other components, disciplined asset disposition can return capital to the next hardware cycle.

Black and Humm close with two questions operators should ask prospective ITAD partners before a major refresh begins: Can I trust you? And can you scale with me?

As GPU infrastructure turns over faster, those questions are likely to become a much larger part of data center operations.

As AI workloads continue to reshape the data center landscape, operators are looking for practical ways to evolve existing infrastructure without overbuilding for tomorrow. In this conversation, we explore how intelligent rack power infrastructure can help data centers support both traditional and AI workloads while improving visibility, efficiency and scalability.

The discussion covers the role of intelligent monitoring, open integration and rack-level solutions in creating power infrastructure that can adapt as data center requirements continue to change.

AI is changing more than compute—it is changing how the entire physical infrastructure of the data center must be designed. In this episode, we'll explore why organizations should stop thinking about cabinets, power and cooling as separate decisions and instead view them as an integrated system. We'll discuss how this approach improves efficiency, simplifies deployment and creates a more flexible foundation for high-density AI environments. 

Along the way, we'll examine the evolving role of the IT cabinet, the industry's transition from air cooling to hybrid and liquid cooling, and the practical questions organizations should be asking as rack densities continue to climb. From rear door heat exchangers to long-term thermal management strategies, listeners will gain practical insights into building infrastructure that's ready for the next generation of AI workloads.

Community acceptance may be emerging as one of the most consequential constraints on data center growth.

On this episode of the Data Center Frontier Show, DCF Editor in Chief Matt Vincent speaks with Buddy Rizer, Executive Director of Loudoun County Economic Development, and Adam Waitkunas, founder of Milldam Public Relations, about the rising political and community resistance confronting data center development — and what the industry needs to do differently.

After two decades working with the world’s largest data center market, Rizer said the current level of opposition is unlike anything he has seen before.

“The pushback is universal,” he said. “The talking points are fairly standard from community to community, and it has really become next to impossible to do business.”

Rizer believes the industry’s next major constraint may no longer be purely physical.

“We thought it was going to be power, but it may be community acceptance and political durability.”

The discussion examines how distrust can overwhelm even strong factual arguments. Rizer noted that Loudoun County’s more than 250 data centers collectively use less than 10% of its water system and have generated enormous tax benefits, yet those figures increasingly struggle to break through.

“You can’t change how people think until you change how they feel,” Rizer said.

Waitkunas argues that developers need to begin community engagement much earlier and give residents a meaningful role in shaping Community Benefit Agreements. Those agreements should go beyond financial contributions to schools, parks or community programs and include operating commitments involving issues such as noise, traffic and other local impacts.

Rizer agreed that simply complying with regulations no longer demonstrates partnership.

“When the noise ordinance says 55 and they come in at 54.5, that to me, that’s not partnership.”

The guests also discuss industry “unforced errors,” perceptions of secrecy surrounding anonymous LLCs and project filings, the growing influence of organized opposition groups, and the risk of companies waiting until a moratorium is already underway before attempting serious community outreach.

For Rizer, developers increasingly need to manage two distinct measures of success.

“Economic success and community trust are two different balance sheets,” he said. “Industry has to invest in both.”

The conversation also explores the role of local governments, particularly smaller communities encountering hyperscale development for the first time; the value of bringing officials and residents through operating facilities that resemble what is actually being proposed; and whether the data center industry ultimately needs a formal standard for community engagement.

Both guests expect conditions to become more difficult before they improve.

Waitkunas anticipates more moratoriums without significant changes in industry behavior, while Rizer warned that data centers could increasingly become central issues in local political campaigns.

“AI hasn’t really created this conversation,” Rizer said, “but it definitely has put it on fast forward.”

The central question for the industry is increasingly straightforward: not whether data centers have impacts, but whether developers can understand those impacts, mitigate them, communicate them honestly and build enough community trust to sustain the infrastructure expansion now underway.

Optics is no longer a supporting accessory in the data center network. As AI infrastructure advances from 400G and 800G toward 1.6-terabit connectivity, optical components are consuming a larger share of network cost, power and operational risk.

In this episode of the Data Center Frontier Show, DCF Editor in Chief Matt Vincent speaks with Bill Gartner, Senior Vice President and General Manager of Cisco’s Optical Systems and Optics business, about how AI is changing the strategic role of optics.

Gartner explains that optics represented roughly 10% of a network port’s bill of materials at 10G. At 400G and above, the optics can cost more than the switch port itself. Reliability has also become critical: A single unstable link can force GPUs operating in parallel to stop, return to a checkpoint and restart. According to data Cisco has seen from hyperscale customers, link flaps can reduce GPU infrastructure efficiency by as much as 40%.

The conversation maps the AI network across three distinct tiers:

Scale-up: Connections within the rack, carrying approximately 500 times the bandwidth of a traditional WAN environment.

Scale-out: Connections between racks, commonly using 400G and 800G pluggable optics.

Scale-across: Coherent optical connections between data centers as AI clusters expand beyond the power limits of a single facility.

Gartner also discusses Cisco’s 1.6T roadmap, routed optical networking, coherent pluggable optics and the emerging debate around co-packaged and near-packaged optics. These architectures promise lower power consumption and greater density, but introduce new questions involving interoperability, replacement and operational resilience.

Looking ahead, Gartner emphasizes that optics is not constraining AI network growth. It is enabling clusters to scale across racks, campuses and geographically distributed data centers, while the coming inference wave shifts the industry’s focus toward cost and power efficiency.