Posts tagged Data Centers

For the last decade, the direction in enterprise infrastructure has seemed pretty set - move to the public cloud, shut down the server room, and don’t look back. That trend is getting more complicated. As AI workloads multiply and cloud costs climb with them, some organizations are bringing part of their infrastructure back in house, while edge computing keeps expanding because the workloads can't tolerate a round trip to a third party’s data center.

The Cloud-Only Model Is Being Reconsidered

The assumption that centralizing everything in the public cloud would automatically be cheaper and more efficient no longer holds up the way it once did. CIO's recent coverage of this shift makes the point. As AI drives demand for specialized, next-generation hardware, cloud provision often isn't the most cost-effective option it used to be. Returning workloads back from the public cloud is already underway at many organizations. Few IT leaders today see an all-in-cloud future for their organization. A blend of cost pressure, privacy requirements, legislation, and the need for operational flexibility is pushing companies toward owning more of their own infrastructure again.

Cost is only part of it. Data sovereignty and regulatory obligations are pushing in the same direction. It's often easier to manage that risk internally than to depend entirely on a third party's controls. Add in sustainability commitments that are straining under the power demands of AI, and the appeal of infrastructure you fully control becomes easier to understand.

None of this means the cloud is going away. It remains the right tool for scalable, well-organized workloads and centralized storage. The real shift is that cloud is becoming one option among several.

The AI Factor Nobody Can Ignore

AI is reshaping this conversation on both sides of the equation. Specialized AI hardware doesn't always make economic sense to rent indefinitely from a cloud provider. On the other hand, AI workloads are also a big part of why the underlying infrastructure question is getting harder, not easier. Brookings' recent research on the future of data centers lays out just how significant the resource demands have become. Data centers already account for a notable share of U.S. electricity consumption. That share is expected to climb sharply as AI adoption accelerates, with some projections putting AI's share of global electricity use as high as a fifth of total demand by the end of the decade. Water use is a growing constraint too, with some facilities drawing hundreds of thousands of gallons a day in regions where water is already scarce.

Every organization weighing on-prem, colocation, or cloud for AI workloads is also weighing exposure to power availability, water availability, and the increasingly complex supply chains for the copper, steel, and semiconductors those facilities depend on.

Resilience and Sovereignty Are Driving the Conversation as Much as Cost

Organizations want to know that a disruption at one provider, one region, or one supplier doesn't take down their entire operation. They want assurance that sensitive data is subject to the laws and controls they choose, not the ones that happen to apply wherever a hyperscaler's region sits. And they want the flexibility to shift workloads as costs, regulations, and business needs change — something that's much harder to do once you're deeply embedded in a single provider's ecosystem.

This is also why data portability deserves more attention than it usually gets. Being able to move data and models between platforms without excessive friction isn't just a technical asset. It's what keeps optionality alive as the infrastructure landscape keeps shifting under our feet.

Where This Leaves IT Leadership

The organizations getting this right are the ones treating infrastructure as a mixed portfolio: cloud for elastic, well-structured workloads; colocation or owned data center capacity for AI, compliance-sensitive, or cost-predictable workloads; and edge for anything where latency is non-negotiable.

Getting that mix right requires a comprehensive look at total cost of ownership — not just monthly cloud spend, but power, staffing, and the opportunity cost of skills gaps that are already showing up across the industry as data center talent gets harder to find.

Peter CavicchiaSeptember 28, 2026Data Centers

Why Power Is the New Constraint in Data Center Strategy

The Electricity Reckoning

For decades, data center operators competed on connectivity, latency, and redundancy. Today, a new variable has moved to the top of the site-selection checklist: access to electricity. The explosive growth of AI workloads has transformed power availability from a background planning assumption into the primary strategic constraint facing the industry — and the fintech firms that depend on it.

The scale of projected demand is staggering. Goldman Sachs Research forecasts that global power consumption from data centers will grow by as much as 165% by 2030 compared to 2023 levels. More recent estimates suggest that figure could reach 220% as AI server shipments exceed earlier projections. Avid Solutions, citing Goldman Sachs Research, notes that data centers will require approximately $6.7 trillion in investment by 2030 to match growing compute power needs — the largest infrastructure investment cycle in modern history. In the United States alone, data centers are projected to account for 8% of total national power demand by the end of the decade, up from roughly 3% in 2022.

Grid Constraints and Interconnection Delays

The problem is not simply one of scale — it is one of timing and geography. AI data centers create unusually concentrated, around-the-clock electrical loads. Unlike residential or industrial demand, which fluctuates throughout the day, AI facilities run at maximum draw continuously. These concentrated 24/7 loads stress grid planning assumptions that were designed for a very different demand profile.

Deloitte's 2025 AI Infrastructure Survey of 120 US data center and power company executives found that grid stress was the leading challenge for data center infrastructure development, with 72% of respondents rating power and grid capacity constraints as very or extremely challenging. Perhaps most strikingly, there is currently a seven-year wait on some requests for grid interconnection — meaning that data centers in planning today may not be able to secure power access until well into the 2030s. Deloitte estimates that US AI data center power demand could grow more than thirtyfold between 2024 and 2035, reaching 123 gigawatts from just 4 gigawatts today.

Infrastructure planning is struggling to keep pace. Goldman Sachs Research estimates that approximately $720 billion in grid spending will be needed through 2030, and that US utilities will need to invest around $50 billion in new generation capacity just to support data center load growth. New pipeline capacity will also be required, as incremental data center power consumption is expected to drive around 3.3 billion cubic feet per day of additional natural gas demand by 2030.

Risk Management Implications for Fintech Leaders

For fintech executives, the power constraint is not just an infrastructure problem — it is a risk management challenge. Business continuity plans that assume reliable, scalable compute availability must now account for the possibility of power-driven capacity shortfalls. A firm whose cloud provider or colocation partner cannot expand its footprint due to grid interconnection delays faces real exposure to latency, throughput, and uptime risk at exactly the moment when AI systems are becoming operationally critical.

The constraint also reshapes competitive dynamics. Avid Solutions highlights that power constraints, not capital limitations, represent the main bottleneck for building new data centers. This means that well-capitalized technology firms with long-term power agreements and dedicated facilities will have structural advantages over firms that rely on spot capacity or shorter-term contracts. For fintech companies that have not yet locked in infrastructure partnerships, the window for securing favorable, long-term compute access may be narrowing.

Proactive fintech leaders are beginning to treat power access as a strategic input, alongside capital, talent, and regulatory positioning. Understanding where compute capacity is being built, how it is being powered, and what risks surround its availability is no longer the exclusive domain of the data center team — it is a board-level concern.

Citations

Avid Solutions. "13 Data Center Growth Projections That Will Shape 2026–2030." Avid Solutions, January 2026. https://avidsolutionsinc.com/13-data-center-growth-projections-that-will-shape-2026-2030/

Goldman Sachs. "How AI Is Transforming Data Centers and Ramping Up Power Demand." Goldman Sachs Insights, 2025. https://www.goldmansachs.com/insights/articles/how-ai-is-transforming-data-centers-and-ramping-up-power-demand

Goldman Sachs. "AI to Drive 165% Increase in Data Center Power Demand by 2030." Goldman Sachs Insights, February 2025. https://www.goldmansachs.com/insights/articles/ai-to-drive-165-increase-in-data-center-power-demand-by-2030

Deloitte. "Can US Infrastructure Keep Up with the AI Economy?" Deloitte Insights, June 24, 2025. https://www.deloitte.com/us/en/insights/industry/power-and-utilities/data-center-infrastructure-artificial-intelligence.html

Serverwala. "Data Centers and Fintech: Powering Financial Innovation." LinkedIn Pulse. https://www.linkedin.com/pulse/data-centers-fintech-powering-financial-innovation-serverwala-saisc

Peter CavicchiaJuly 22, 2026Data Centers, Electrical Grids

Sustainable Data Centers as a Competitive Advantage

The race to build next-generation data centers is no longer decided by compute density alone. Sustainability has emerged as a decisive selection criterion—one that touches operating costs, regulatory exposure, investor expectations, and long-term resilience. For enterprises and regulated financial firms evaluating colocation or build-to-suit options, a facility’s environmental profile is now as material as its uptime record.

The Scale of the Problem

Data centers are voracious consumers of resources. Beyond the enormous electricity demands required to power thousands of servers, facilities can consume between one and five million liters of water per day—a volume that strains communities already experiencing drought, particularly across the American Southwest. As machine learning workloads and large language model inference continue to scale, those demands will only intensify. Harvard SEAS researchers studying the challenge noted that advanced computing tasks “need more and more computing power,” driving the need for more data center capacity—and with it, a proportionate growth in carbon emissions.

Four Levers for Greener Operations

Research from Harvard’s John A. Paulson School of Engineering and Applied Sciences identifies four primary engineering levers that data center operators can pull to reduce environmental impact: alternative energy generation, cooling efficiency, waste-heat recycling, and improved water management.

Cooling is the most immediate target. Conventional air-circulation systems account for roughly 40 percent of a typical facility’s electricity consumption, much of it wasted on components that generate little heat. Newer direct-to-chip cooling—where coolant chills metal plates placed against the highest-heat components—can substantially cut that load. The shift toward liquid cooling is already underway, and facilities that adopt it early gain a durable power-usage efficiency (PUE) advantage over peers.

Waste-heat reuse turns a liability into an asset. Dublin provides a leading example: an Amazon facility is redirecting thermal exhaust to supply space heating and hot water for public buildings and housing. Operators that quantify and monetize their waste heat unlock an additional revenue stream while reducing net carbon output—an argument that resonates with both ESG-focused boards and local regulators.

Renewable energy procurement completes the picture. Interactive siting tools can overlay transmission infrastructure with solar, wind, and small modular nuclear reactor potential, helping operators identify locations where clean power is both available and affordable. Water stewardship—mapping local supply constraints before breaking ground—rounds out the discipline, reducing the risk of regulatory friction or community opposition.

From ESG Checkbox to Competitive Moat

Leading colocation providers are turning sustainability commitments into measurable business advantages. Digital Realty, for example, has issued $7.2 billion in green bonds and secured 1.5 gigawatts of contracted solar and wind capacity. Its US portfolio is 69 percent ENERGY STAR-certified by managed IT capacity, and it has certified more than 15 million square feet to LEED, BREEAM, and IGBC standards—with 61 percent achieving Gold or higher. The U.S. EPA has listed the company among the top ten largest buyers of renewable energy nationally. Those credentials are not merely marketing; they represent verifiable cost structures and risk profiles that enterprise procurement and compliance teams can audit.

For regulated financial firms, the stakes are even higher. Energy-efficient facilities with verifiable green certifications translate directly to lower Scope 2 emissions disclosures, stronger alignment with SEC climate-risk reporting requirements, and reduced exposure to future carbon pricing. Investors increasingly scrutinize infrastructure vendors through the same ESG lens they apply to portfolio companies, making a data center partner’s sustainability credentials a factor in due diligence.

Ultimately, sustainable data center design is not a concession to environmental sentiment—it is an engineering and financial discipline. Facilities that consume less energy, manage water intelligently, reuse waste heat, and source power renewably will carry lower operating costs, attract better financing, and face fewer regulatory headwinds than those that do not. In a market where differentiation is hard-won, sustainability is becoming one of the clearest signals of operational excellence.

Peter CavicchiaJune 17, 2026Data Centers, Big Data, Sustainable Data Center Design

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