Podcast: Phill Lawson-Shanks, Chief Innovation Officer, Aligned Data Centers

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Podcast: Phill Lawson-Shanks, Chief Innovation Officer, Aligned Data Centers

In the latest episode of the Data Center Frontier Show podcast, DCF Editor-in-Chief Matt Vincent sits down with Phill Lawson-Shanks, Chief Innovation Officer at Aligned Data Centers, for a wide-ranging discussion that touches on some of the most pressing trends and challenges shaping the future of the data center industry. From the role of nuclear […]

From the role of nuclear energy and natural gas in addressing the sector’s growing power demands, to the rapid expansion of Aligned’s operations in Latin America (LATAM), in the course of the podcast Lawson-Shanks provides deep insight into where the industry is headed.

Scaling Sustainability: Tracking Embodied Carbon and Scope 3 Emissions

A key focus of the conversation is sustainability, where Aligned continues to push boundaries in carbon tracking and energy efficiency. Lawson-Shanks highlights the company’s commitment to monitoring embodied carbon—an effort that began four years ago and has since positioned Aligned as an industry leader.

“We co-authored and helped found the Climate Accord with iMasons—taking sustainability to a whole new level,” he notes, emphasizing how Aligned is now extending its carbon traceability standards to ODATA’s facilities in LATAM. By implementing lifecycle assessments (LCAs) and tracking Scope 3 emissions, Aligned aims to provide clients with a detailed breakdown of their environmental impact.

“The North American market is still behind in lifecycle assessments and environmental product declarations. Where gaps exist, we look for adjacencies and highlight them—helping move the industry forward,” Lawson-Shanks explains.

The Nuclear Moment: A Game-Changer for Data Center Power

One of the most compelling segments of the discussion revolves around the growing interest in nuclear energy—particularly small modular reactors (SMRs) and microreactors—as a viable long-term power solution for data centers. Lawson-Shanks describes the recent industry buzz surrounding Oklo’s announcement of a 12-gigawatt deployment with Switch as a significant milestone, calling the move “inevitable.”

“There are dozens of nuclear plants operating in the U.S. today, but people just don’t pay much attention to them,” he says. “Companies like Oklo are designing advanced modular reactors that are walk-away safe, reuse spent fuel, and eliminate the risks associated with traditional light-water reactors. This is the path forward.”

However, he acknowledges that the widespread adoption of nuclear will take time, given the regulatory hurdles of the Nuclear Regulatory Commission (NRC) and the challenges of getting sites certified. Still, he remains optimistic: “We need this, and as an industry, we’re pre-buying energy because we see the challenges ahead.”

Bridging the Energy Gap with Natural Gas and Hydrogen

While nuclear is a long-term solution, data centers need reliable power sources today. Lawson-Shanks sees natural gas as a practical interim solution, provided emissions can be mitigated. He also points to hydrogen as an emerging technology with potential, though challenges remain.

“Hydrogen is really an energy transportation methodology rather than an energy source,” he explains. “It’s highly corrosive, and the infrastructure isn’t fully in place yet, but it’s something we’re closely monitoring.”

He predicts that natural gas reciprocating engines will serve as a bridge solution until nuclear modules become widely available. “Once we reach steady-state nuclear power, those gas engines could replace diesel generators, which we all want to phase out,” he says.

Explosive Growth in LATAM and the Evolution of Aligned’s Global Strategy

The conversation also covers Aligned’s expansion into Latin America following its acquisition of ODATA. Lawson-Shanks describes the region as a booming market, particularly in Brazil, where Aligned has access to renewable energy through its investment in wind farms.

“LATAM is an enormous growth market, and our waterless cooling system is ideal for places like Santiago, where water scarcity makes evaporative cooling unfeasible,” he explains.

Aligned is integrating its advanced cooling technologies—such as Delta³ and DeltaFlow—into ODATA’s new facilities, ensuring that sustainability remains a core component of their LATAM operations.

Innovating Beyond Cooling: The Future of Heat Reuse

Another forward-looking topic is Aligned’s interest in heat reuse, an area where Lawson-Shanks sees significant potential for innovation. Through its partnership with QScale in Canada, Aligned is exploring methods to capture and repurpose waste heat from data centers for other applications.

“Their heat reuse strategy is really interesting, and we’re looking at how we can implement similar solutions in North America,” he says, hinting at future developments to come.

Looking Ahead: A Future Shaped by Innovation and Sustainability

As the conversation wraps up, it’s clear that Lawson-Shanks sees the data center industry at an inflection point. The combination of sustainability commitments, new energy technologies, and rapid global expansion is forcing companies to rethink traditional models and embrace innovation at an unprecedented scale.

“We’ve always fought against the idea that data centers have to be built the same way they were in the 1970s,” he says. “We’re constantly redesigning, rethinking how we procure energy, and pushing the industry forward.”

With Aligned continuing to lead the charge in sustainability, energy innovation, and international expansion, the insights shared in this episode offer a compelling look at the challenges and opportunities ahead for the data center industry.

Here’s a timeline of the podcast’s key moments:

After introductions, exciting news about Lawson-Shanks and Aligned joining the 2025 DCF Trends Summit Editorial Advisory Board is shared. 0:02
Lawson-Shanks discusses the industry’s sustainability focus. The impact of ChatGPT on market dynamics is highlighted. 2:21
The rapid growth of cloud deployment is highlighted. Challenges in supply chain management due to factory shutdowns are discussed. 3:26
The emergence of agentic AI systems is brought up. The importance of proximity to cloud instances for effective data processing is emphasized. 4:49
A potential edge boom in 2025 is speculated upon. The construction of facilities for AI inference aligned with cloud interests is questioned. 7:06
Lawson-Shanks explains how a significant land grab for data center space has occurred. He describes how existing data centers are unable to accommodate new high-density paths. 8:20
On how the Aligned design architecture includes adaptive data center features. High-density cooling solutions are being implemented with liquid and air. 8:54
On how the demand for technology is increasing exponentially, and more space and technology will be required to meet future needs. 11:44
An overview of Open Compute Project (OCP) architecture is provided. The architecture includes discrete components for flexibility. 13:22
The importance of adhering to OCP standards is emphasized. Such adherence ensures safety and efficiency in data center operations. 14:09
A discussion about the critical role of data centers in industrial revolutions is presented. Data centers are described as essential infrastructure for modern technology. 17:14
Discussion now centers on the future of nuclear energy. The potential for small modular reactors is highlighted. 18:42
The importance of addressing public fears about radiation is emphasized. The benefits of advanced reactor designs are noted. 19:55
Concerns about energy transmission infrastructure are raised. The discussion notes that building new transmission lines can take decades. 21:16
Natural gas is discussed as a near-green energy source. Mitigation strategies for emissions are mentioned. 22:54
Hydrogen’s role as an energy transportation method is explored. The challenges of biofuel supply and infrastructure are highlighted. 23:36
Innovative approaches to data center design and energy procurement are emphasized. The importance of adapting to new methodologies is noted. 25:15
The need for tracking embodied carbon is highlighted. The discussion reveals how this initiative has been ongoing for four years and has led to significant developments. 27:28
The expansion of Aligned’s carbon tracking to ODATA in Latin America is discussed. This includes providing clients with lifecycle assessments and environmental product declarations. 27:53
The growth of the market in Latin America, especially in Brazil, is emphasized. The presence of green energy sources, such as wind farms, is noted as a positive factor. 29:24

DCF Show Podcast Quotes from Phill Lawson-Shanks, Chief Innovation Officer, Aligned Data Centers

On Market Demand and the Evolution of Data Centers

“Existing data centers in major metros are largely full, and many weren’t designed for the high-density workloads we’re seeing today.”
“The industry went through a phase where we were just stamping out the same boxes—buying land, building infrastructure. Now, there are real engineering challenges again, and that’s exciting.”
“We’re in an unprecedented time. The use of technology isn’t slowing down—it’s accelerating, and we need more space, more innovation, more infrastructure to support it.”
“AI isn’t just a trend—it’s a fundamental shift, and data centers have to evolve to support that scale.”

On Aligned’s Adaptive Data Center Architecture

“We designed our adaptive data center architecture so that we can integrate both air and liquid cooling seamlessly.”
“Our Delta Cube arrays allow us to do high-density cooling with just air. But for the foreseeable future, we will need both air and liquid cooling.”
“Liquid to the chip removes most of the heat—maybe 70-80%—but there are still DIMMs, storage arrays, and network components that require airflow.”
“We’re building infrastructure that has to last 20 to 30 years. That means designing for today’s workloads while being adaptable for future technologies.”

On Engineering Challenges and Innovation

“We’re designing for everything from 50 megawatts with air to 360 megawatts with liquid cooling, all in a redundant fashion.”
“We’re rethinking everything—electrical infrastructure, cooling, heat rejection, and even heat reuse. There are exciting possibilities ahead.”
“The reality is, these racks are huge now. They come pre-populated, they’re heavy, and they need to be moved safely. Many older data centers just weren’t designed with that in mind.”

On the Open Compute Project (OCP) and Industry Standards

“OCP started with Facebook—now Meta—disaggregating servers into their core components. It’s changed the way hyperscalers build infrastructure.”
“We worked closely with OCP to help define and ratify a data center standard for hyperscalers. That means clients know our facilities conform to those specifications from the start.”
“Something as simple as ensuring the right door heights, corridor angles, and loading capabilities makes a huge difference when deploying large-scale infrastructure.”

On Industry Leadership and Open Innovation

“All boats rise. We lead, but we don’t want to be exclusive—we want to pull the industry forward with us.”
“I started at Compaq, and they had a philosophy: Identify gaps in the market, solve them, patent the solution, and then release it to the industry. We take the same approach—innovation that benefits everyone.”
“Data centers are the engine of the fourth and now the fifth industrial revolution. They are critical infrastructure for everything we do.”

On the Growing Role of Nuclear Energy in Data Centers

“I think it’s inevitable. Absolutely inevitable.”
“There are dozens of nuclear plants across the U.S., but people just don’t pay that much attention to them.”
“I personally love the advanced modular reactors—Oklo in particular. They reuse spent fuel, they’re walk-away safe, and there’s no pressurization risk.”
“You could hug one of these things for a year and receive less radiation than I got flying across the country last night.”
“The biggest challenge isn’t generation—it’s transmission. It takes about 12 years to build out the infrastructure to actually pass electrons.”
“Some of the high-tension lines going into Virginia now were approved 25 years ago. That’s how long these things take.”
“Nuclear is classified as green energy, and all our energy is 100% renewable. This is the future for the whole industry.”

On Natural Gas and the Transition to Cleaner Power

“Natural gas isn’t green, but you can mitigate its impact. It’s what we have available to bridge the shortfall until nuclear modules are online.”
“We’re looking at natural gas reciprocating engines as a stopgap until we get steady-state, utility-grade nuclear power.”
“Eventually, I see those gas engines replacing the diesel generators we have today—because we all want to get away from that.”
“Hydrogen is interesting, but it’s really more of an energy transport method than a true energy source. There are still major challenges with its infrastructure and supply.”

On Data Center Innovation and Industry Change

“The traditional way of building data centers was designed in the 1970s during the golden age of the mainframe. And for years, everyone just kept doing the same thing.”
“At Aligned, we tore up the rulebook. We constantly rethink how we build, design, and procure energy.”
“We lead, but we also push the industry forward—we don’t just follow the predefined supply chain that’s existed for decades.”

On Aligned’s Acquisition of ODATA and Expansion in LATAM

“We acquired them over a year ago, but they’re very much an Aligned company. We let that amazing team run their business as they need to, while helping them leverage the core competencies that got us to where we are today.”
“Their new buildings will be designed around our methodologies—using Delta³ and DeltaFlow where appropriate.”
“LATAM is an enormous growth market. Brazil, in particular, is seeing extraordinary expansion, with strong green energy sources from wind farms.”
“Chile is still growing, and our waterless cooling system is ideal for Santiago, where water is too scarce to use for evaporative heat rejection.”

On Embodied Carbon and Sustainability Leadership

“Four years ago, we saw the need to start tracking embodied carbon. We’ve been doing that ever since, and it’s driven a lot of industry progress.”
“We co-authored and helped found the Climate Accord with iMasons—taking sustainability to a whole new level.”
“We’re now extending our carbon traceability standards to ODATA in LATAM, tracking second and third life for key components and providing clients with true Scope 3 carbon assessments.”
“North America is still behind the rest of the world in creating lifecycle assessments and environmental product declarations. Where gaps exist, we look for adjacencies and highlight them—helping move the industry forward.”

On QScale and Heat Reuse Innovation

“Our relationship with QScale in Canada is exciting. They’re focused on high-performance compute and are adopting our design methodologies.”
“Their heat reuse strategy is really interesting. We’re exploring ways to capture and repurpose waste heat in North America as well.”

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To close industry watchers, it’s really no secret that the AI infrastructure race has entered another phase; one where capital formation itself may become as strategically important as GPUs, power procurement, or liquid cooling. And in launching Helix Digital Infrastructure, investment giant KKR is making a calculated wager that hyperscalers no longer simply need developers or financiers. They need a partner capable of orchestrating capital, energy, connectivity, and data center execution as a unified platform. The significance of that strategy is underscored by the executive chosen to lead it. Adam Selipsky, the former CEO of Amazon Web Services and one of the industry’s most experienced cloud operators, will serve as Co-Founder and CEO of Helix, bringing firsthand experience from the very class of customers the new venture intends to serve. A New Model for AI Infrastructure Helix launches with more than $10 billion in long-duration committed capital from founding investors including KKR, the Kuwait Investment Authority (KIA), NVIDIA, and Vistra. But the headline number tells only part of the story. The company has been structured around an increasingly important thesis: that AI infrastructure can no longer be assembled piecemeal. Rather than treating data centers, electrical supply, transmission capacity, and fiber connectivity as separate procurement exercises, Helix proposes a vertically coordinated approach in which a single organization manages and finances the entire infrastructure stack. According to KKR, the objective is to reduce execution risk and accelerate deployment for hyperscale customers facing unprecedented AI demand. As AI factories grow from hundreds of megawatts toward gigawatt-scale campuses, synchronization among land acquisition, utility planning, financing, construction, and technology deployment has emerged as one of the industry’s defining challenges. Helix is effectively positioning itself as an operating platform designed to simplify that complexity. Why Selipsky Matters The appointment of Adam Selipsky may be the announcement’s

Beyond Hyperscale: Why Enterprise Data Centers Still Matter in the AI Era

“The enterprise data centers, even the new ones, tend to be far, far smaller than new hyperscale deployments,” Killian said. “Not uncommon to see enterprises deploy a quarter meg or one meg or two, maybe up to 10 megs. Whereas the hyperscale guys are deploying 40 up to 300 meg facilities.” But scale alone does not tell the story. For every one of the roughly 20 hyperscale users that dominate headlines, Killian noted, there may be 50 to 100 times as many large and mid-sized enterprise users. Those companies run critical business systems, purchase hardware, software, telecom and services, employ large data center teams, and often operate multiple facilities across domestic, edge, EMEA and Asia-Pacific footprints. In other words, enterprise demand may be smaller in unit size, but it remains massive in aggregate. And as AI shifts from training to inference, the enterprise data center could become newly strategic. Enterprise AI Is Not Hyperscale AI Killian’s central point is that enterprise infrastructure requirements differ materially from hyperscale requirements. Hyperscalers are primarily optimizing for massive scale and speed to market. Enterprises, by contrast, tend to prioritize reliability, flexibility, integration into broader IT systems, and audit and compliance. That difference has major implications for developers and colocation providers. “The real industry opportunity is to take some of the innovation and the economies of scale that we’re seeing from the hyperscale builds to deliver smaller chunks of data center capacity,” Killian said. That might mean adapting lessons from 40 MW or 100 MW campuses into enterprise-ready deployments of 2 MW, 4 MW or 8 MW. Killian pointed to providers such as DataBank and Flexential as examples of companies working to deliver hyperscale-derived efficiencies in smaller enterprise increments. He also noted that QTS and other large campus developers may reserve portions of multi-building campuses

Revolutionizing Data Center Cooling: Innovations for AI and HPC Growth

This is a crucial point for AI infrastructure. In some markets, water can be as politically and operationally difficult as power. Evaporative cooling and cooling towers can consume large volumes of water, while discharge permits can slow projects or limit operations. Gradiant claims HyperSolved can expand access to alternative sources such as municipal reuse and impaired supplies, reduce reliance on freshwater, protect cooling performance through integrated treatment and AI-enabled operations, and minimize discharge through high-recovery concentration and reuse. The platform uses containerized systems for immediate or temporary capacity while also supporting permanent infrastructure and lifecycle operations from commissioning onward. That fits the AI data center buildout, where developers may need bridge capacity during construction, phased water infrastructure, or interim systems while permanent treatment plants are completed. This can address the speed of deployment issue that plagues many data center solutions. Water is becoming a siting and scaling variable that has to be addressed. A site may have land and power prospects, but if water sourcing, reuse, or discharge cannot be solved, the project will face higher costs, delays, and local opposition. Gradiant is positioning itself as the managed water layer for hyperscale AI, similar to how power providers, cooling vendors, and network suppliers each own critical infrastructure domains. The Pattern: Hybridization, Standardization, and Industrial Scale The announcements included here make it clear that cooling is seeing significant attention from technology vendors, and not just state-of-the-art new technologies such as direct-to-chip, but also traditional data center air cooling. T-Global and SiPearl are working on high-conductivity materials and two-phase modules for HPC chips. Castrol is providing fluids for direct-to-chip and immersion environments. These are technologies aimed at the heat source itself, where higher chip power and rack density are overwhelming conventional approaches. The reference design offerings from Johnson Controls acknowledges the importance

Microsoft will invest $80B in AI data centers in fiscal 2025

And Microsoft isn’t the only one that is ramping up its investments into AI-enabled data centers. Rival cloud service providers are all investing in either upgrading or opening new data centers to capture a larger chunk of business from developers and users of large language models (LLMs). In a report published in October 2024, Bloomberg Intelligence estimated that demand for generative AI would push Microsoft, AWS, Google, Oracle, Meta, and Apple would between them devote $200 billion to capex in 2025, up from $110 billion in 2023. Microsoft is one of the biggest spenders, followed closely by Google and AWS, Bloomberg Intelligence said. Its estimate of Microsoft’s capital spending on AI, at $62.4 billion for calendar 2025, is lower than Smith’s claim that the company will invest $80 billion in the fiscal year to June 30, 2025. Both figures, though, are way higher than Microsoft’s 2020 capital expenditure of “just” $17.6 billion. The majority of the increased spending is tied to cloud services and the expansion of AI infrastructure needed to provide compute capacity for OpenAI workloads. Separately, last October Amazon CEO Andy Jassy said his company planned total capex spend of $75 billion in 2024 and even more in 2025, with much of it going to AWS, its cloud computing division.

John Deere unveils more autonomous farm machines to address skill labor shortage

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Self-driving tractors might be the path to self-driving cars. John Deere has revealed a new line of autonomous machines and tech across agriculture, construction and commercial landscaping. The Moline, Illinois-based John Deere has been in business for 187 years, yet it’s been a regular as a non-tech company showing off technology at the big tech trade show in Las Vegas and is back at CES 2025 with more autonomous tractors and other vehicles. This is not something we usually cover, but John Deere has a lot of data that is interesting in the big picture of tech. The message from the company is that there aren’t enough skilled farm laborers to do the work that its customers need. It’s been a challenge for most of the last two decades, said Jahmy Hindman, CTO at John Deere, in a briefing. Much of the tech will come this fall and after that. He noted that the average farmer in the U.S. is over 58 and works 12 to 18 hours a day to grow food for us. And he said the American Farm Bureau Federation estimates there are roughly 2.4 million farm jobs that need to be filled annually; and the agricultural work force continues to shrink. (This is my hint to the anti-immigration crowd). John Deere’s autonomous 9RX Tractor. Farmers can oversee it using an app. While each of these industries experiences their own set of challenges, a commonality across all is skilled labor availability. In construction, about 80% percent of contractors struggle to find skilled labor. And in commercial landscaping, 86% of landscaping business owners can’t find labor to fill open positions, he said. “They have to figure out how to do

2025 playbook for enterprise AI success, from agents to evals

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More 2025 is poised to be a pivotal year for enterprise AI. The past year has seen rapid innovation, and this year will see the same. This has made it more critical than ever to revisit your AI strategy to stay competitive and create value for your customers. From scaling AI agents to optimizing costs, here are the five critical areas enterprises should prioritize for their AI strategy this year. 1. Agents: the next generation of automation AI agents are no longer theoretical. In 2025, they’re indispensable tools for enterprises looking to streamline operations and enhance customer interactions. Unlike traditional software, agents powered by large language models (LLMs) can make nuanced decisions, navigate complex multi-step tasks, and integrate seamlessly with tools and APIs. At the start of 2024, agents were not ready for prime time, making frustrating mistakes like hallucinating URLs. They started getting better as frontier large language models themselves improved. “Let me put it this way,” said Sam Witteveen, cofounder of Red Dragon, a company that develops agents for companies, and that recently reviewed the 48 agents it built last year. “Interestingly, the ones that we built at the start of the year, a lot of those worked way better at the end of the year just because the models got better.” Witteveen shared this in the video podcast we filmed to discuss these five big trends in detail. Models are getting better and hallucinating less, and they’re also being trained to do agentic tasks. Another feature that the model providers are researching is a way to use the LLM as a judge, and as models get cheaper (something we’ll cover below), companies can use three or more models to

OpenAI’s red teaming innovations define new essentials for security leaders in the AI era

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More OpenAI has taken a more aggressive approach to red teaming than its AI competitors, demonstrating its security teams’ advanced capabilities in two areas: multi-step reinforcement and external red teaming. OpenAI recently released two papers that set a new competitive standard for improving the quality, reliability and safety of AI models in these two techniques and more. The first paper, “OpenAI’s Approach to External Red Teaming for AI Models and Systems,” reports that specialized teams outside the company have proven effective in uncovering vulnerabilities that might otherwise have made it into a released model because in-house testing techniques may have missed them. In the second paper, “Diverse and Effective Red Teaming with Auto-Generated Rewards and Multi-Step Reinforcement Learning,” OpenAI introduces an automated framework that relies on iterative reinforcement learning to generate a broad spectrum of novel, wide-ranging attacks. Going all-in on red teaming pays practical, competitive dividends It’s encouraging to see competitive intensity in red teaming growing among AI companies. When Anthropic released its AI red team guidelines in June of last year, it joined AI providers including Google, Microsoft, Nvidia, OpenAI, and even the U.S.’s National Institute of Standards and Technology (NIST), which all had released red teaming frameworks. Investing heavily in red teaming yields tangible benefits for security leaders in any organization. OpenAI’s paper on external red teaming provides a detailed analysis of how the company strives to create specialized external teams that include cybersecurity and subject matter experts. The goal is to see if knowledgeable external teams can defeat models’ security perimeters and find gaps in their security, biases and controls that prompt-based testing couldn’t find. What makes OpenAI’s recent papers noteworthy is how well they define using human-in-the-middle

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