Skip to content
MarketScale
‹ Back to IndustriesSoftware & Technology

Execution at Scale: How Applied Digital Is Powering AI Infrastructure in Ellendale

AI infrastructure is rapidly evolving, with companies like Applied Digital focusing on executing AI-ready data centers at scale. These facilities must accommodate increasing power densities, implement new cooling technologies, and function in unconventional locations like Ellendale, North Dakota. The discussion highlights the challenges and strategies required for efficient execution and operation of these high-density environments.

This story was produced through MarketScale. See how Software & Technology teams put it to work with Executive Thought Leadership.

Promoted content from Applied Digital on MarketScale.

By Software And Technology · Ai Data CenterAi InfrastructureApplied DigitalHigh-density Data Center
Share

Key takeaways

01

AI infrastructure is evolving rapidly, focusing on executing data centers at scale.

02

Demand for AI-ready facilities necessitates adaptation to high power densities and new technologies.

03

Effective execution involves balancing cost, resilience, and sustainability in challenging conditions.

AI infrastructure is evolving at breakneck speed, and the real challenge is no longer just designing next-generation data centers—it’s executing them at scale. As demand for AI-ready facilities grows, operators must adapt to immense increases in power density, new cooling technologies, and unconventional deployment locations. Power density requirements for AI workloads are pushing the limits of traditional data center design, forcing operators to rethink everything from electrical infrastructure to thermal management systems.

So, what does it really take to run a high-density, liquid-cooled, AI-ready data center in a rural region like Ellendale, North Dakota? How do leaders balance execution, cost, resilience, and sustainability under these extreme conditions?

On this episode of Architects of Acceleration, host Philbert Shih, Founder and Managing Director of Structure Research, sits down with Laura Laltrello, Chief Operating Officer at Applied Digital, to explore how execution works at scale for Polaris Forge—a 100-megawatt AI-ready data center. From contingency planning to liquid cooling and rural workforce development, Laura shares how her team is overcoming infrastructure and operational challenges to bring AI workloads to life.

Highlights from the Episode:

  • Operating in High-Density AI Environments: AI data centers like Polaris Forge are moving from 4–9 kW per rack to 100–130 kW. This shift demands a radical rethink of cooling—from traditional air to precision-engineered liquid systems—and redefines what “mission-critical operations” really mean.
  • Leveraging Location for Efficiency: North Dakota’s climate provides up to 220 days of “free cooling,” driving PUE down to 1.18. Combined with access to stranded wind power and a closed-loop water system, the data center achieves up to $85 million in annual savings compared to traditional facilities.
  • Planning for the Unplannable: With 14-foot snow drifts, remote access, and no legacy data center workforce, Laura details how Applied Digital blends community integration, smart tech, and internal simulations like “What Could Go Wrong” days to bulletproof the facility against disruptions.

Laura Laltrello is the Chief Operating Officer at Applied Digital. With a robust background in infrastructure operations, she brings decades of experience navigating complex, high-stakes environments. Known for her pragmatic approach and passion for building resilient teams, Laura has been instrumental in designing and launching one of the industry’s most efficient AI-ready data centers. Her work draws on deep cross-sector insights and a history of successful leadership in both technology and operations.

Part of this channel

Applied Digital

News, updates, and expert insights from Applied Digital.

Visit the channel →

About the author

SA
Software And Technology

Software & Technology: are you visible to AI?

Before they reach out, Software & Technology buyers ask AI engines which vendors to trust. See how AI describes your company today, and where competitors show up instead.

Free workspace

You just read one Software & Technology expert. Imagine publishing your whole team.

This article was produced through MarketScale. Create a free workspace and turn your own team's Software & Technology expertise into the articles, video, and social content B2B marketing buyers in your industry are searching for. No credit card, no demo required.

NPS +73 · 1,000+ creators · 38+ countries

What you get, free

Your own MarketScale Studio workspace
One video edit a month, on us
AI writing, editing, and publishing tools
In-platform coaching to learn the system

More Software & Technology Insights

AI governance gaps are blocking enterprise scale-up across the Middle East

AI governance gaps are blocking enterprise scale-up across the Middle East

AI governance challenges are preventing many businesses in the Middle East from scaling up their AI deployment. While technology advancements are not a barrier, the lag in internal governance frameworks is slowing down AI adoption. Addressing these governance gaps can accelerate the integration of AI within enterprises.

  • 01AI adoption in the Middle East is hindered by outdated internal governance frameworks.
  • 02Technology is not the limiting factor for AI deployment; governance is.
  • 03Improving governance frameworks can accelerate AI scale-up in enterprises.

Jul 21, 2026

Palo Alto Networks CEO puts a number on the AI cost problem: 90% token price drop needed

Palo Alto Networks CEO puts a number on the AI cost problem: 90% token price drop needed

Nikesh Arora, CEO of Palo Alto Networks, stated that for enterprise AI to scale, token costs must decrease by 90% within two years. He highlighted that high costs have already impacted companies like Uber, which spent its full-year AI budget by April.

  • 01Token costs for AI need to decline by 90% in two years for scalability.
  • 02Uber exhausted its annual AI budget by April due to high costs.

Jul 20, 2026

Kaspersky selects WebEngage for B2B marketing automation, treating data governance as a procurement requirement

Kaspersky selects WebEngage for B2B marketing automation, treating data governance as a procurement requirement

Kaspersky has partnered with WebEngage to automate its B2B marketing efforts. The selection process involved stringent evaluations similar to those used for security products, ensuring data governance and secure access are fundamental components from the outset.

  • 01Kaspersky selected WebEngage for its B2B marketing automation needs.
  • 02Data governance and secure access were key factors in the procurement process.
  • 03WebEngage was vetted with the same rigor as a security product.

Jul 20, 2026

Explore More Software & Technology Insights

Read more expert perspectives from across Software & Technology.

Browse Software & Technology Hub

About the Experts

SA
Software And Technology
PS
Philbert Shih

Founder and Managing Director

Structure Research

LL
Laura Laltrello

Chief Operating Officer

Applied Digital

For B2B teams

Your experts could be publishing here

Stories like this one run on content MarketScale captures from real practitioners. See how your team's expertise becomes coverage in Software & Technology and beyond.

Book a 15-minute demo

Or call us. No forms required. We pick up. 214-945-2512