IT Infrastructure Investment Analysis

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

Excited to share our latest analysis on #AI's impact on data center investment strategies. This deep dive explores: - The strategic advantages and limitations of #REITs vs direct ownership - How capital requirements shape investment decisions in AI-ready facilities - Why operational control affects long-term value creation - What passive vs active management means for AI infrastructure adaptability Power constraints are reshaping the data center investment landscape. With AI deployments driving 10x higher rack densities, your investment approach matters more than ever. Here's what's at stake: Consider a #hyperscale AI deployment requiring 100MW. Through a REIT, you gain quick market access and liquidity, but limited control over power infrastructure and cooling solutions. Direct ownership demands higher capital but enables purpose-built AI infrastructure. Northern Virginia's power constraints now drive premium valuations for AI-ready facilities. While REITs offer immediate exposure to this market, direct investors targeting emerging regions with abundant power can potentially capture higher long-term returns. When investment strategy aligns with power availability and AI infrastructure requirements, investors position themselves for sustainable growth in this rapidly evolving sector. Which approach fits your investment strategy? Read the full article to explore the detailed analysis of REIT and direct ownership paths in the AI-driven data center landscape. #datacenters

AI and Cloud investments are surging in lockstep 📊 as companies ruthlessly reallocate IT budgets for 2025. BCG's latest data shows tech leaders are aggressively funding AI (48% increasing spend) and cloud services (36% growing) while simultaneously slashing legacy infrastructure budgets. This insight comes from Boston Consulting Group (BCG)'s just-released IT Spending Pulse—a major survey of 602 tech leaders conducted in December. The elephant in the room: this predated US tariffs, but the fundamental direction of travel remains clear and compelling. ⚡ What's fascinating is how #AI, #cloud, and security are growing hand-in-hand, creating a powerful flywheel effect. To fully leverage AI capabilities, companies must consolidate their data and modernize infrastructure—driving cloud migration and creating demand for enhanced security. This virtuous cycle explains why these three categories dominate spending increases while traditional categories face deep cuts. “Cloud services and security infrastructure are indispensable for scaling, resilience, and safe and reliable operations. They’re prerequisites for unleashing transformative technologies like AI.” - BCG 🔄 Perhaps most interesting is the ongoing vendor consolidation trend Organizations are actively reducing vendor counts in nearly every area EXCEPT AI—where 50% are expanding their roster while just 20% are consolidating. For established technologies, companies are moving toward integrated solutions over patchworks of standalone tools. 🛒 Here's why cloud marketplaces are becoming mission-critical for software sellers: They perfectly align with this dual strategy. As buyers consolidate vendors and optimize spend, marketplaces offer a streamlined procurement channel where they can leverage existing cloud commitments for third-party purchases—creating a win-win for both buyers and sellers in this new landscape. 💲 For those questioning the AI investment surge, the ROI data is staring to look appealing: High-maturity AI companies are seeing 15% returns—nearly 70% higher than limited adopters. Even more telling, AI agents are delivering 13.7% ROI, outperforming traditional GenAI applications. With AI adoption reaching 80% of surveyed companies and 58% already implementing AI agents, the message is clear: companies not prioritizing AI-cloud integration risk falling behind competitors who are reaping measurable rewards from their investments. 📈 This is precisely why we're launching our "2025 State of Cloud Marketplace & Co-Sell" research with Clazar As software sellers scramble to align with these new buyer priorities, data on what's working in cloud GTM has never been more valuable. Our comprehensive study dive into tactics that correlate most with marketplace success and why some teams drive >20% of revenue via marketplaces while others stall. Live launch on April 24: https://hubs.ly/Q03fKS200 Join our webinar on what's actually working for top-performing Cloud GTM teams

Visualizing Big Tech Company Spending On AI Data Centers Summary: Major tech companies are investing aggressively in AI data centers to meet the surging demand for computational power, driven by advanced AI workloads. Here’s an overview of their spending as of August 2024: Key Financial Insights: Microsoft leads in total AI spending, with $46 billion in combined capital expenditures (capex) and operating costs (opex). It has 300 data centers globally. Meta follows with $27 billion, Google with $33 billion, and Amazon with $19 billion in total spending. Capital expenditures, including GPUs and infrastructure, dominate expenses for all companies, reflecting the upfront cost of building AI capabilities. Training vs. Inference Costs: Training costs are currently double inference costs for Google and Amazon. Training requires significant computational resources and energy, involving GPUs and large datasets. As AI deployments increase, inference costs are expected to surpass training expenses, similar to trends observed with OpenAI’s ChatGPT. Future Projections: Microsoft and BlackRock’s $100 billion Global Artificial Intelligence Infrastructure Investment Partnership (GAIIP) highlights future ambitions to expand AI infrastructure, emphasizing both computing and energy systems. Takeaway: Big tech’s AI strategies are marked by massive upfront investments in infrastructure and growing operational expenses. As AI workloads scale, efficient management of inference costs will be pivotal for sustained profitability. Source: https://lnkd.in/gicFRnQN #BigTech #AIDatacenters #TechSpending #ArtificialIntelligence #GPUs #AIInfrastructure #MicrosoftAI #MetaAI #GoogleAI #AmazonAI #AITraining #DataCenterEfficiency #Sustainability #TechInvestments #GAIIP