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Virginia’s Loudoun County Grapples with Future of Data Centers as New Developments Continue Statewide

Where Economic Growth Meets Sustainability The data center industry’s contributions to local economies are undeniable. From job creation to substantial tax revenues, these facilities have reshaped Virginia’s economic landscape. Loudoun County alone hosts 199 operational data centers, with another 148 applications under review. The economic growth in ongoing data center development has spread out across […]

Where Economic Growth Meets Sustainability

The data center industry’s contributions to local economies are undeniable. From job creation to substantial tax revenues, these facilities have reshaped Virginia’s economic landscape. Loudoun County alone hosts 199 operational data centers, with another 148 applications under review.

The economic growth in ongoing data center development has spread out across the state even as it’s remained close to Data Center Alley. The ongoing growth underscores the demand for the infrastructure to support the digital economy, while highlighting ways forward and also challenges in sustainability and community compatibility. A pair of recent examples in the news exemplify this trend.

TECfusions Grows In Clarksville

In Clarksville, Virginia in far southern Mecklenburg County, TECfusions is spearheading innovative AI data center development. Backed by a $300 million loan agreement to be used for the development and expansion of its site there, the company’s flagship facility aims to meet the increasing demands of AI workloads.

Not simply growth to meet projected demand, the TECfusion expansion is a result of an urgent capacity requirement from one of their key tenants. 

According to a November press release by TECfusions:

In response to urgent capacity needs from a key tenant, gradual funding began in January 2024 and has now been solidified in a formal loan agreement, which includes the cumulative monies invested earlier. To date, $160 million has been allocated towards construction, with the remaining funds earmarked for completing Phase I of the Clarksville facility.

According to the company’s development timline, the site’s phased build-out is projected to reach 37.5 megawatts (MW) of capacity upon completion of the Clarksville data center’s Hall D. 

With the funding spanning a 15-year term, Mike Picchi, CFO of TECfusions, commented on its alignment with the company’s long term goals and meeting the needs of tenants:

“This agreement fully funds our Clarksville Phase I buildout and aligns perfectly with our long-term growth strategy, demonstrating the economic vitality of our approach and opening the doors for future expansion projects. With tenants that require immediate, scalable data center capacity, this funding enables us to meet that demand efficiently to ensure rapid deployment of capacity for today’s digital world.”

The company said that funds will be strategically allocated across several key initiatives, including AI-ready infrastructure deployment, on-site sustainable power generation solutions, and site infrastructure development. The investment is also expected to have a significant positive impact on the local community, creating numerous jobs in construction and operations while substantially expanding the region’s digital infrastructure and tax base.

Significantly, in being designed to house one of the world’s largest GPU clusters, TECfusions emphasizes that its adaptive reuse model exemplifies a sustainable approach, converting existing facilities into state-of-the-art data centers. This strategy not only accelerates deployment timelines but also minimizes environmental impact.

Iron Mountain Adds 350 MW of Data Center Capacity Across VA

Similarly, Iron Mountain’s recent expansion in Richmond and Manassas, with the company acquiring two new data center sites, highlights the Virginia data center industry’s rapid and ongoing scaling.

Iron Mountain is adding over 350 MW of planned capacity across the two new sites, which bring more than 100 acres to the company’s data center development portfolio.

The 66-acre site in Richmond is planned to become a 200 MW data center campus. With over 200 MW of expected capacity, Iron Mountain says its new Richmond campus “will be perfectly suited for highly regulated customers, thanks to its rigorous compliance program,” which will encompass: HIPAA, FISMA High, PCI-DSS, ISO 27001, ISO 50001, SOC2/3, among other codes.

The new Iron Mountain Richmond campus will be situated at the White Oak Technology Park in Henrico County, a unique business park with more than 2,200 acres for technology and data center campuses. Richmond has a robust power and network infrastructure, positioned along the I64 and I95 corridors, connecting to Northern Virginia and the subsea fiber cable landings in Virginia Beach.

For its part, the 40 acre site in Manassas will allow expansion of the existing 142-acre Iron Mountain campus there, which offers over 2 million square feet of energy-efficient space, with two new buildings, and potentially an additional 150 MW of capacity.

This acquisition includes the planned development of an electricity substation to ensure continued uninterrupted power supply across the Manassas campus.

Leveraging investment by energy providers to modernize transmission and distribution infrastructure, and a close partnership with local economic development authorities, Iron Mountain says its commitment to Virginia offers its customers secure, sustainable data centers that meet strict government regulations, all while benefiting from smart property tax savings.

The new developments promise significant economic benefits, including job creation and enhanced tax bases, while adhering to stringent sustainability standards, such as 100% renewable energy usage.

Mark Kidd, Executive Vice President and General Manager, Asset Lifecycle Management and Data Centers, Iron Mountain, said:

“The Commonwealth of Virginia has abundant infrastructure, a highly skilled workforce, strong fiber connectivity, and is a pro-business community – making it an ideal location to support our commitment to investing in high-growth markets that help drive our expansion strategy. As a leading data center provider, we’re excited to offer further critical capacity to our retail and hyperscale customers where and when they need it most.”

Points of Contention

While data centers bring economic advantages, their environmental and spatial footprints cannot be ignored, and have been continual points of contention with local government. These facilities consume vast amounts of electricity and require substantial land, often sparking debates over resource allocation.

In Loudoun County, for instance, Commission Chair Michelle Frank highlighted concerns about losing thriving businesses to data center developments, noting that skyrocketing land costs driven by data center demand could squeeze out other industries.

Proponents of data centers, however, argue that technological advancements and strategic planning can mitigate these issues.

Companies like TECfusions and Iron Mountain are pioneering energy-efficient designs and sustainable power generation solutions. These measures not only reduce carbon footprints but also align with broader environmental goals, ensuring that data centers remain viable in the long term.

The Path Forward: Zoning and Strategic Development

The future of data center development in Virginia hinges on thoughtful planning and regulatory clarity. As highlighted by Rizer and other stakeholders, identifying zones suitable for data centers is a critical step.

This approach would provide business owners with stability while safeguarding community interests. It would also prevent data centers from encroaching on residential areas or displacing other industries, as seen in recent debates over developments near Goose Creek and the Arcola area.

Moreover, collaboration between government bodies and industry leaders is essential. A letter sent to the commission on November 26th from County Chair Phyllis Randall and Transportation and Land Use Committee Chair Michael Turner underscores the urgency of reaching a consensus on zoning amendments.

Their proposed joint meetings between the Board of Supervisors and the Planning Commission aim to expedite decision-making, ensuring that regulatory changes reflect the county’s broader goals.

Innovative Models for Growth

Beyond zoning and regulation, the data center industry’s growth in Virginia offers an opportunity to embrace innovative development models. Adaptive reuse, as demonstrated by TECfusions, can serve as a blueprint for future projects. By repurposing existing structures, this approach not only accelerates deployment but also reduces the environmental impact of new construction.

Additionally, leveraging renewable energy and sustainable practices can address concerns about electricity consumption. Iron Mountain’s commitment to renewable energy and efficient cooling techniques exemplifies how data centers can align with environmental objectives. These innovations not only benefit the planet but also enhance the industry’s reputation, fostering goodwill among local communities and policymakers.

The evolution of data centers in Virginia reflects broader trends shaping the digital economy. As local governments navigate the challenges of zoning, regulation, and community impact, the need for collaboration and forward-thinking strategies becomes increasingly evident.

By balancing economic growth with sustainability and community well-being, Virginia can continue to lead in data center development, setting an example for regions worldwide.

JLARC Report

The Joint Legislative Audit & Review Commission of the Virginia legislature recently released a report on the impact of data centers on the state. This detailed review of data center impact (over 150 pages) covers everything from land use issues, to sustainability, water, and power impact.

The legislative report concludes that development of data centers in Virginia could triple the state’s energy demands if unconstrained. As succinctly reported by Virginia Mercury‘s Charlie Paullin:

“The report is in line with a recent regulatory filing from Dominion Energy stating annual increases in electric power demand would be relatively flat, if it weren’t for data centers […] Modelling from E3, a third-party consultant, showed that energy demand for the state would increase from just over 10,000 gigawatt hours in 2023 to just over 30,000 gigawatt hours by 2040, if data center development didn’t have to deal with constraints, including needing energy requirements like transmission lines to be available prior to coming online. 

Without data center development, the demand increased to about 12,500 gigawatt hours […] To meet those demands, more renewable energy facilities like solar and offshore will be needed, but so will natural gas, JLARC’s report stated, which would amount to a new plant being built every one and a half years, approximately […] ither meeting the full unconstrained demand, or half of it, relies on offshore wind and nuclear technology, which JLARC stated could come from the “unproven” small modular reactor technology.”

While we will be further covering the content of the JLARC report in an upcoming story, the nutshell is this: the report found that data centers provide a positive impact to Virginia’s economy, though it is mostly during the initial construction. And in the end, the success of this endeavor will depend on the ability of stakeholders to find common ground.

Whether through zoning reforms, innovative development models, or enhanced sustainability measures, the future of data centers lies in their capacity to adapt to changing demands while remaining rooted in the communities they serve.

Softening NIMBY in VA

And while NIMBY issues often dominate local politics, the development of data centers, with their global footprint, is slowly changing the perspective some Virginia communities have on their development.

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BP Halts Share Buybacks

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Transmission at the Breaking Point: Why the Grid Is Becoming the Defining Constraint for AI Data Centers

Regions in a Position to Scale California (A- overall)California continues to lead in long-term, scenario-based transmission planning. CAISO’s most recent transmission plan identifies $4.8 billion in new projects to accommodate approximately 76 gigawatts of additional capacity by 2039, explicitly accounting for data center growth alongside broader electrification. For data center developers, California’s challenge is less about planning quality and more about execution. Permitting timelines, cost allocation debates, and political scrutiny remain significant hurdles. Plains / Southwest Power Pool (B- overall, A in regional planning)SPP stands out nationally for embracing ultra-high-voltage transmission as a backbone strategy. Its recent Integrated Transmission Plans approve more than $16 billion in new projects, including multiple 765-kV lines, with benefit-cost ratios exceeding 10:1. This approach positions the Plains region as one of the most structurally “AI-ready” grids in North America, particularly for multi-gigawatt campuses supported by wind, natural gas, and emerging nuclear resources. Midwest / MISO (B overall)MISO’s Long-Range Transmission Planning framework aligns closely with federal best practices, co-optimizing generation and transmission over long planning horizons. While challenges remain—particularly around interregional coordination—the Midwest is comparatively well positioned for sustained data center growth. Regions Facing Heightened Risk Texas / ERCOT (D- overall)Texas has approved massive new transmission investments, including 765-kV projects tied to explosive load growth in the Permian Basin. However, the report criticizes ERCOT’s planning for remaining largely siloed and reliability-driven, with limited long-term scenario analysis and narrow benefit assessments. For data centers, ERCOT still offers speed to market, but increasingly with risks tied to congestion, price volatility, and political backlash surrounding grid reliability. Southeast (F overall)The Southeast receives failing grades across all categories, with transmission development remaining fragmented, utility-driven, and largely disconnected from durable regional planning frameworks. As AI data centers increasingly target the region for its land availability and tax incentives, the lack of

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

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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

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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

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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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