How AI Influences Global Data Center Markets

Data Center Growth Is Accelerating—But It's What Sits Around the Racks That Wins the Margin The installed global data center capacity is projected to surge to 114.3 GW by 2025, growing at a +17.7% CAGR since 2021 (IEA). That translates to 485.4 terawatt-hours of electricity consumption—or 1.7% of the planet’s total demand. We’re seeing a fundamental reordering of digital infrastructure economics. What’s Driving It? Cloud: Enterprise migration is still in early innings. Gartner estimates that less than 50% of enterprise workloads have moved to the cloud. The runway is long. AI: McKinsey projects that AI workloads alone could require 50 GW of incremental capacity by 2030, adding more demand in five years than all of global hyperscale growth from 2015–2020 combined. Edge—or a logical shift to underserved metros: As Accenture notes, workloads and AI inference engines are driving demand into tier 2 and tier 3 metros, reshaping where capital needs to flow. 🧩 The Investment Insight: The Bottlenecks Become the Profit Pools Yes, installed capacity is rising rapidly—but capital is clustering in hyperscale deployments with increasingly compressed margins. The real margin opportunity is forming around the friction points: 1. Power availability and efficiency With many grids facing constraint, EY notes that renewable-backed and dispatchable power procurement strategies are becoming a strategic differentiator. Developers with energy expertise are now drawing infrastructure fund-level investments, not just REIT or data center capital. 2. Interconnection & last-mile fiber As workloads fragment and move outward, the physical and logical edge gains value. Dense interconnection hubs, metro fiber providers, and programmable routing intelligence are becoming supply-side moats. 3. Market ecosystems & orchestration platforms McKinsey highlights that fragmented value chains in digital infrastructure are creating "integration deserts". As quoting, fulfillment, and SLA management stretch across multiple providers, multi-party platforma and orchestration layers—akin to Amazon in e-commerce—are starting to centralize fragmented workflows. 4. Data intelligence & automation Accenture’s Infrastructure Vision 2025 identifies AI-powered operations and smart procurement systems as key value unlocks. Tools that simplify monetization and delivery will define the operating system for digital infrastructure. The Bigger Picture This isn’t just a bet on data centers—it’s a thesis on the unbundling and replatforming of digital infrastructure. The most compelling opportunities won’t be found solely in the four walls of a data center, or in the chips inside it. Instead, they’ll emerge from the data, software, and services layers that monetize and automate digital infrastructure at scale. I am excited for the ecosystem, there is value to be created at a massive scale over the next 5 years. #DigitalInfrastructure #AI #Cloud #DataCenters #ConnectedCommerce #Fiber

So far this year, the U.S. data center landscape is shifting fast. As power constraints tighten in traditional hubs like Northern Virginia and Silicon Valley, secondary and emerging markets are stepping into the spotlight. Do you agree? Here’s what’s driving the shift and where the real opportunities may lie: 👉🏽 Key Trends: • Explosive Growth: U.S. data center inventory jumped 43% year-over-year in Q1 2025. Atlanta and Phoenix are now among the top four markets. • Hyperscaler Expansion: AI and cloud giants are pre-leasing space in non-traditional markets like Columbus, Des Moines, and Reno to secure power and speed to market. • Design Evolution: Liquid cooling and high-density racks are becoming the norm to support AI workloads. But what are the challenges? • Power Scarcity: Grid capacity is maxed in many metros. Transmission delays are pushing timelines into 2027 and beyond. • Construction Bottlenecks: Labor shortages, permitting delays, and rising material costs are slowing builds. • Cooling and Density Challenges: AI workloads demand new cooling strategies and facility designs, especially in retrofitted sites. So, where’s the opportunity? • Emerging Markets: States like Iowa, Indiana, and Ohio offer cheaper, more available power and faster permitting. This is ideal for hyperscaler and co-lo builds. • Behind-the-Meter Solutions: On-site renewables, gas peakers, and early-stage nuclear (SMRs) are gaining traction to bypass grid delays. • Sustainable Infrastructure: Clean energy integration is now a competitive edge. Why does this matter? AI infrastructure here in the U.S. is being built in places we’re only beginning to notice. Maybe even in a county near you! It’s a dynamic space, and I’m keeping a close eye on the trends and opportunities. What are you seeing in your region or sector? Let me know! 👇🏽

The AI Power Paradox: Why Energy Will Determine Who Wins the Next Computing Revolution ⚡ 🧠While everyone debates which AI model will dominate, I’m watching a brewing crisis that could determine the real winners: power infrastructure. ⛔️ Here’s the problem: AI #datacenter power demand could surge more than 30x by 2035, but America’s largest grid operator just delivered a stark warning—“There is simply no new capacity to meet new loads,” said Joseph Bowring president of Monitoring Analytics, the independent watchdog for PJM Interconnection. The numbers tell the story: 📈 • Goldman Sachs Sachs forecasts global data center power demand will increase 165% by 2030 • U.S. Department of Energy (DOE) projects data center load could double or triple by 2028 • #Data centers currently consume 1-2% of global power, rising to 3-4% by decade’s end • Between 2024-2025, data center power usage accounted for $9 billion (174%) of increased power costs in #PJM territory alone. This creates a strategic shift: The companies building #AI infrastructure must now become energy companies. EQT Corporation CEO calls America’s permitting delays a “geopolitical liability”—while we’re stuck in regulatory quicksand, #China accelerates AI infrastructure deployment unconstrained. The AI gold rush is an #energy arms race. What’s your take on the energy-AI nexus? Love to hear your thoughts below ⬇️ 💭 #Nuclear #Utilities

AI data center development is expected to accelerate until the end of the decade, but bottlenecks in data center and GPU deployments are just emerging. Morgan Stanley now forecasts a 23% annual increase in global data center capacity until 2030, with the U.S. at the forefront. However, the main challenge isn’t demand; instead, supply faces ongoing limitations due to government regulations and international supply chain issues, including power, machinery, and materials. Energy remains the main constraint, but it is not the only limiting factor. Permitting processes are slowing down, and building materials are becoming increasingly scarce and costly. Construction expenses are projected to increase by 11% each year, as reported by Morgan Stanley. To meet increasing demand, operators are considering two main options: converting existing Bitcoin mining farms and constructing facilities near nuclear or gas power plants. Sectors and regions such as the Middle East and China, which already have advantages in the data center supply chain, are expected to attract growing strategic interest. Elon and xAI just announced another data center project in Saudi Arabia. Meanwhile, hyperscaler capital expenditures continue to hit new records. Meta has increased its full-year revenue forecast to $64–72 billion. The four largest cloud providers are expected to spend a combined $1 trillion annually by the end of the decade. Additionally, NVIDIA’s GB200/300 order book continues to be revised upward. The worldwide AI infrastructure race is underway. The only true limit is how quickly we WANT to build.