“AI-first infrastructure rollouts — particularly those involving GPUs, edge accelerators, and high-efficiency cooling — are directly in the crosshairs,” Gogia noted. “So are quantum computing R&D efforts and high-reliability storage systems where thermal and magnetic materials matter.” China, responsible for 70% of global rare earth mining output and 87% of refined supply, poses a serious threat to enterprise IT hardware supply chains with these restrictions — especially for companies with AI-optimized server lines. AI chip production under threat The impact on semiconductor manufacturing comes at a critical time when enterprise demand for AI chips is soaring. Companies including Nvidia, AMD, Intel, and TSMC rely on rare earth elements during the manufacturing of advanced chips. “We see the greatest exposure in private data center expansion projects, AI inferencing at the edge, and next-gen device manufacturing, including specialized industrial IoT and robotics,” noted Gogia. Major cloud providers have been aggressively expanding their AI compute capacity, with substantial hardware refreshes planned for late 2025. These plans may now face delays or cost increases as chip manufacturers grapple with supply constraints. Pricing pressures to be felt in 3-6 months The immediate impact is expected to be limited as manufacturers work through existing inventory, but pricing pressure could emerge within 3-6 months, experts feel.

Nord Quantique plans to use the money to expand its team, says Julien Camirand Lemyre, the company’s president, CTO and co-founder. That’s an opportunity to accelerate the development of the technology, he says. “By extension, what this will mean for enterprise users is that quantum solutions to real-world business problems will be available sooner, due to that acceleration,” he says. “And so enterprise customers need to also accelerate how they are thinking about adoption because the advantages quantum will provide will be tangible.” Lemyre predicts that useful quantum computers will be available for enterprises before the end of the decade. “In fact, there has been tremendous progress across the entire quantum sector in recent years,” he says. “This means industry needs to begin thinking seriously about how they will integrate quantum computing into their operations over the medium term.” “We’re seeing, with the deployment of programs like the QBI in the US and investments of billions of dollars from  public and private investors globally, an increasing maturity of quantum technologies,” said Paul Terry, CEO at Photonic, which is betting on optically-linked silicon spin qubits.  “Our architecture has been designed from day one to build modular, scalable, fault-tolerant quantum systems able to be deployed in data centers,” he said. He’s not the only one to mention fault-tolerance. DARPA stressed fault-tolerance in its announcement, and its selections point to the importance of error correction for the future of quantum computing. The biggest problem with today’s quantum computers is that the number of errors increases faster than the number of qubits, making them impossible to scale up. Quantum companies are working on a variety of approaches to reduce the error rates low enough that quantum computers can get big enough to actually to real work.

Zayo Group Holdings Inc. has emerged as one of the most aggressive fiber infrastructure players in North America, particularly in the context of AI-driven growth. With a $4 billion investment in AI-related long-haul fiber expansion, Zayo is positioning itself as a critical enabler of the AI and cloud computing boom. The company is aggressively expanding its long-haul fiber network, adding over 5,000 route miles to accommodate the anticipated 2-6X increase in AI-driven data center capacity by 2030. This initiative comes as AI workloads continue to push the limits of existing network infrastructure, particularly in long-haul connectivity. New Fiber Routes The new routes include critical connections between key AI data center hubs, such as Chicago-Columbus, Las Vegas-Reno, Atlanta-Ashburn, and Columbus-Indianapolis, among others. Additionally, Zayo is overbuilding seven existing routes to further enhance network performance, resiliency, and low-latency connectivity. This new development is a follow-on to 15 new long haul routes representing over 5300 route miles of new and expanded capacity deployed over the last five years. These route locations were selected based on expected data center growth, power availability, existing capacity constraints, and specific regional considerations. The AI Data Center Sector: A Significant Driver of Fiber Infrastructure The exponential growth of AI-driven data center demand means that the U.S. faces a potential bandwidth shortage. Zayo’s investments look to ensure that long-haul fiber capacity keeps pace with this growth, allowing AI data centers to efficiently transmit data between key markets. This is especially important as data center development locations are being driven more by land and power availability rather than proximity to market. Emerging AI data center markets get the high speed fiber they need, especially as they are moving away from expensive power regions (e.g., California, Virginia) to lower-cost locations (e.g., Ohio, Nevada, Midwest). Without the high-speed networking capabilities offered by

Crusoe and the Lancium Clean Campus: A New Model for Power-Optimized Compute Crusoe Energy’s 300-megawatt deployment at the Lancium Clean Campus in Abilene is a significant marker of how data center strategies are evolving to integrate more deeply with energy markets. By leveraging demand flexibility, stranded power, and renewable energy, Crusoe is following a path similar to some of the most forward-thinking projects in the data center industry. But it’s also pushing the model further—fusing AI and high-performance computing (HPC) with the next generation of power-responsive infrastructure. Here’s how Crusoe’s strategy compares to some of the industry’s most notable power-driven data center deployments: Google’s Oklahoma Data Center: Proximity to Renewable Growth A close parallel to Crusoe’s energy-centric site selection strategy is Google’s Mayes County data center in Oklahoma. Google sited its facility there to take advantage of abundant wind energy, aligning with the local power grid’s renewable capacity. Similarly, Crusoe is tapping into Texas’s deregulated energy market, optimizing for low-cost renewable power and the ability to flexibly scale compute operations in response to grid conditions. Google has also been an industry leader in time-matching workloads to renewable energy availability, something that Crusoe is enabling in real time through grid-responsive compute orchestration. Sabey Data Centers in Quincy: Low-Cost Power as a Foundation Another instructive comparison is Sabey Data Centers’ Quincy, Washington, campus, which was built around one of the most cost-effective power sources in the U.S.—abundant hydroelectric energy. Sabey’s long-term strategy has been to co-locate power-intensive compute infrastructure near predictable, low-cost energy sources. Crusoe’s project applies a similar logic but adapts it for a variable grid environment. Instead of relying on a fixed low-cost power source like hydro, Crusoe dynamically adjusts to real-time energy availability, a strategy that could become a model for future power-aware, AI-driven workloads. Compass and Aligned: Modular, Energy-Adaptive

For the third installment of our Executive Roundtable for the First Quarter of 2025, we asked our panel of seasoned industry experts about how the dynamics of data center site selection have never been more complex—or more critical to long-term success. In an industry where speed to market is paramount, operators must now navigate an increasingly constrained landscape in the age of AI, ultra cloud and hyperscale expansion, marked by fierce competition for land, tightening power availability, and evolving local regulations.  Traditional core markets such as Northern Virginia, Dallas, and Phoenix remain essential, but supply constraints and permitting challenges are prompting developers to rethink their approach. As hyperscalers and colocation providers push the boundaries of site selection strategy, secondary and edge markets are emerging as viable alternatives, driven by favorable energy economics, infrastructure investment, and shifting customer demand.  At the same time, power procurement is now reshaping the equation. With grid limitations and interconnection delays creating uncertainty in major hubs, operators are exploring new solutions, from direct utility partnerships to on-site generation with renewables, natural gas, and burgeoning modular nuclear concepts. The question now is not just where to build but how to ensure long-term operational resilience. As data center demand accelerates, operators face mounting challenges in securing suitable land, reliable power, and regulatory approvals in both established and emerging markets.  And so we asked our distinguished executive panel for the First Quarter of 2025, with grid capacity constraints, zoning complexities, and heightened competition shaping development decisions, how are companies refining their site selection strategies in Q1 2025 to balance speed to market, scalability, and sustainability? And, which North American regions are showing the greatest potential as the next wave of data center expansion takes shape?

For this episode of the DCF Show podcast, host Matt Vincent, Editor in Chief of Data Center Frontier, is joined by Santiago Suinaga, CEO of Infrastructure Masons (iMasons), to explore the urgent challenges of scaling data center construction while maintaining sustainability commitments, among other pertinent industry topics. The AI Race and Responsible Construction “Balancing scale and sustainability is key because the AI race is real,” Suinaga emphasizes. “Forecasted capacities have skyrocketed to meet AI demand. Hyperscale end users and data center developers are deploying high volumes to secure capacity in an increasingly constrained global market.” This surge in demand pressures the industry to build faster than ever before. Yet, as Suinaga notes, speed and sustainability must go hand in hand. “The industry must embrace a build fast, build smart mentality. Leveraging digital twin technology, AI-driven design optimization, and circular economy principles is critical.” Sustainability, he argues, should be embedded at every stage of new builds, from integrating low-carbon materials to optimizing energy efficiency from the outset. “We can’t afford to compromise sustainability for speed. Instead, we must integrate renewable energy sources and partner with local governments, utilities, and energy providers to accelerate responsible construction.” A key example of this thinking is peak shaving—using redundant infrastructure and idle capacities to power the grid when data center demand is low. “99.99% of the time, this excess capacity can support local communities, while ensuring the data center retains prioritized energy supply when needed.” Addressing Embodied Carbon and Supply Chain Accountability Decarbonization is a cornerstone of iMasons’ efforts, particularly through the iMasons Climate Accord. Suinaga highlights the importance of tackling embodied carbon—the emissions embedded in data center construction materials and IT hardware. “We need standardized reporting metrics and supplier accountability to drive meaningful change,” he says. “Greater transparency across the supply chain can be