Infrastructure Investment Insights

Infra IPOs have quietly dominated app/SaaS IPOs since 2017. Top performers: CrowdStrike, Snowflake, Cloudflare, Zscaler, Datadog, Rubrik, Okta, MongoDB. ⸻ Why infrastructure is harder: • Deep-tech R&D and heavy upfront cap-ex • 6-12-month pilots + complex compliance hurdles • Requires rare talent and extreme buyer trust Most startups stall before true product–market fit. ⸻ Why infrastructure is bigger: • Live in the plumbing → become the default • High switching costs & sticky usage expansion • Gross margins widen at scale → giant cash engines ⸻ Proof points • Cybersecurity: Wiz, Cyera, Chainguard — all <5 yrs old, already $4-30 B EV. Security budgets compounding 15-20 % YoY. • Data & cloud: Snowflake (IPO ’20) → ~$70 B. CrowdStrike (IPO ’19) → ~$117 B. TAM grows with every new workload. • AI infra: OpenAI ~$300 B, Anthropic ~$61 B — tracking toward the most valuable companies ever. ⸻ Pattern: 🏗 Hard build → 📈 Steep adoption → 🔒 Durable moat → 💰 Massive outcome. Founders and investors who can navigate infrastructure’s tougher early cycle stand to capture outsized, enduring value. #Infrastructure #Cloud #Cybersecurity #AI #Startups #VC

I was dead wrong about data centers... When I started investing in data centers, I dismissed them as "fancy warehouses with good air conditioning." Today, they're at the heart of cloud computing, AI, and global connectivity, and I've spent years catching up to this remarkable evolution. My journey began with a painful truth: - Experience in digital infrastructure? Considerable. - Data center expertise? Practically zero. - Global sector trends and market growth drivers? A complete mystery. During an initial assessment of a hyperscale data center project in West Africa, reality hit me. As we analyzed the development process, reviewed customer pipelines, and evaluated operating KPIs and valuation metrics, I realized: "This isn't just real estate, this is the new utility of the digital age." Everything changed when we abandoned three critical misconceptions: 1. "Data centers are an opportunistic play" 2. "Enterprise colocation is the primary growth driver" 3. "Emerging markets will follow developed market patterns" Instead, we embraced a more forward-looking, strategic approach: focus on markets with the right combination of cloud demand, infrastructure, and regulatory environment that have or will attract hyperscale investment. While others hesitated, we moved decisively, examining power availability, fiber connectivity, and policy frameworks to identify tomorrow's data center hubs. Our methodology transformation: - Analyzed global sector trends comprehensively - Identified the most promising markets - Understood that hyperscalers were driving unprecedented demand The results were significant: 1. Increased exposure to the sector 2. A more diversified global data center portfolio across regions 3. Strategic diversity across data center types and financing instruments The most powerful insight? The old metrics ($/kW, occupancy rates, EBITDA multiples) are dangerously limited. What matters is understanding global sector trends and market-specific dynamics that drive sustainable growth. For those navigating this space, focus on: 1. Understanding global growth drivers and their regional impacts 2. Viewing these assets through an infrastructure lens, not just real estate 3. Mastering the unique economics and KPIs of the sector What has been your experience in the data center sector? #datacenters #ifcinfrastructure

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

🚀 Unveiling Hidden Gems in the Digital Infrastructure Boom 🏗️ While the headlines often go to the big names—Amazon, Microsoft, Google; some of the most exciting innovation and momentum is coming from under-the-radar players helping build the AI-powered, cloud-connected world we’re racing into. According to a new post from Data Center Dollars, here are a few standouts shaping the next wave of infrastructure growth: 🔍 Emerging Players in AI & Data Center Development 🏭 New Era Helium + Sharon AI – Building a 250MW net-zero AI facility in West Texas, targeting completion by 2026. Hydrogen cooling + helium adjacency = serious potential. 💧🧠 💻 CoreWeave – From crypto to AI infrastructure leader. Operating 32+ data centers, including a $1.6B supercomputer campus for $NVDA in Texas. Full hyperscale energy. ⚡📊 🌍 Global Hotspot to Watch: Brazil 🇧🇷 ⚡ 90% of Brazil’s electricity is renewable 🌞 Amazon, Microsoft, and others are expanding cloud campuses here, drawn by its clean energy advantage and regional demand 🧱 Behind the Build: Construction & Materials Leaders 🔹 $MLM (Martin Marietta Materials) – Benefiting from booming demand for concrete & aggregates 🔹 $FLR (Fluor Corp) – Global EPC player building massive data center campuses 🏗️🌎 📈 Investor Angle: Data Center REITs & Infra Funds 🏢 $EQIX (Equinix) & $DLR (Digital Realty) – Blue-chip exposure to global demand for cloud, AI, and interconnection 💼 $IRM (Iron Mountain) – From records to racks—investing big in digital 💰 $DBRG (DigitalBridge) – Focused on next-gen digital infra: fiber, edge, towers, and yes—AI-ready data centers 🌏 $GDS (GDS Holdings) – China’s largest domestic hyperscale developer, now expanding into Southeast Asia 📄 Full post: https://lnkd.in/eYKS-gyc #AI #DataCenters #DigitalInfrastructure #Hyperscale #REITs #TechInvesting #CleanEnergy #EmergingMarkets #DataCenterConstruction #InfraBoom

5 BRUTAL LESSONS I learned from $500M infrastructure deals (that no one warns you about) I’ve sat inside infra finance rooms where hundreds of millions were on the table. And here’s the truth: The finance model isn’t what wins the deal. The signal speed does. Over the past 10+ years in finance, I’ve worked across capital projects where the stakes were sky-high and time was short. The mistakes weren’t always big. But they were expensive. If you’re a CFO or VP of Finance in infrastructure, here are 5 lessons I’d take into every deal from now on. Lesson 1️⃣ : Your forecast is only as good as your last assumption. In one real estate infrastructure deal, the finance team used a 6-month-old utility rate assumption for a 20-year lease model. Inflation and regional rate changes quietly added $1.2M in cost exposure to the OpEx model. No one noticed until the financing terms were signed. The spreadsheet worked. The assumption didn’t. Lesson 2️⃣ : If you’re updating manually, you’re already behind. We reviewed a construction project where material costs had spiked 9% over 30 days - but the budget hadn’t been updated because it took 10 days to rerun the forecast. That lag caused a vendor escalation, a late payment penalty, and burned 11% of contingency before the CFO even saw the overage. Manual means reactive. Reactive means margin loss. Lesson 3️⃣ : Cost overruns never start as overruns. They start as exceptions. One late permit. One re-quoted trenching package. One crew that goes overtime. But by the time they show up in your model, the overrun has already happened. AI helps here - not by making new models, but by catching exceptions as they form. Lesson 4️⃣ : “Clean reporting” doesn’t mean you’re in control. I worked with a VP Finance who presented spotless dashboards every quarter. On paper, everything looked fine. But their rolling cash flow forecast missed three vendor shifts and 2 scheduling delays. When the CEO asked why they were pulling from the credit line mid-project, the answer was simple: “Our data was clean. Our insight wasn’t.” Lesson 5️⃣ : Speed creates trust. When ops knows that finance can catch drift early, they partner. When they think finance is 2 weeks behind, they stop sharing. In one logistics company, we plugged AI into the forecast engine. - CapEx drift was flagged in 36 hours. - Project leads started proactively requesting re-forecasts. - Finance stopped defending and started leading. If you take nothing else from this, take this: Accuracy doesn’t build trust. Responsiveness does. In high-stakes deals, timing is everything. Lag is the real liability. Want to see how we help infra finance teams cut signal lag in 90 days or less? → Repost this if you’ve seen even one of these play out → DM me “Lessons” and I’ll send over the full breakdown → Follow @LylyaTsai for weekly playbooks on forecasting, AI, and finance strategy in infra

Spending time in DC for the #SpringMeetings was a timely reminder of both the urgency and opportunity in accelerating climate-aligned investment—especially in emerging markets and developing economies (#EMDEs). Here are five takeaways that stood out: 💡 1. The infrastructure gap is real—but investable. Demand for resilient, low-carbon infrastructure is rising fast. But the pipeline isn't keeping pace—not due to a lack of viable projects, but because critical enablers like transmission, storage, and digital systems are still missing. Fixing these structural gaps is key to unlocking capital. 💸 2. Risk perception still outweighs reality. Clean energy investments in EMDEs are often high-performing. Yet financing remains scarce. Our newly published paper on the #CostofCapital in EMDEs shows how misaligned #risk perceptions—driven by outdated models and high transaction costs—continue to inflate financing costs and stall investment, even when the fundamentals are strong. 📉 3. Sovereign credit ratings and transparency are make-or-break. Ratings still shape market access and pricing. But current #methodologies don’t always reflect long-term reforms or sustainability progress. A shift toward greater transparency and forward-looking indicators could significantly lower borrowing costs for countries making real strides. 🔄 4. Blended finance must move beyond signaling. We heard this loud and clear: #BlendedFinance has catalytic potential, but only if structured to scale. That means designing deals around investor needs—right-sizing, risk clarity, and standardized data are non-negotiables. 📊 5. Data platforms are redefining the playing field. New tools are emerging that let investors map opportunities to climate strategies using advanced taxonomies and geographic overlays. Precision matters—and connecting mandates to real-economy solutions is how we move from billions to trillions. Thanks to Investor Leadership Network, The Rockefeller Foundation, IFC - International Finance Corporation, Princeton Sovereign Finance Lab, and Dalberg for the thought-provoking sessions and collaborative energy. 📄 Read more in our new paper: https://lnkd.in/ecZ5zvgy #InfrastructureInvestment #CostOfCapital #SovereignRatings #EnergyTransition #EmergingMarkets #Transparency #SpringMeetings

#AI, the transition to the #cloud, and increasingly connected consumers are generating so much data that the world will need not only more #datacenters, but more electricity to power those data centers. This has been one of the most-discussed topics in infrastructure, but we think our take on the issue is differentiated. I address this and more in my latest KKR Market Review, particularly how we’re seeing a convergence of two critical #infrastructure investment themes: #digitalization and the #energytransition. A few key takeaways from the report: 🔹 Supported by transformative technologies like AI, the increased demand for data creates a compelling backdrop to invest in the hard assets enabling the digital ecosystem. This starts with data centers, but also includes fiber optic networks, wireless towers, and other assets. 🔹 Large-scale investment in both power generation and transmission will be needed to solve the digital power problem, along with new technology and creative solutions. We believe this will lead to an increase in energy transition investments and technologies, as well as ongoing opportunities in conventional energy. 🔹 The digital power problem presents a massive challenge that requires scaled capital and deep sector expertise to solve. As a top 3 private infrastructure investor, we feel we are well-positioned to provide solutions. For more, you can give it a read here: https://go.kkr.com/493nRHb

Few people know infrastructure investing like Marc Ganzi, the CEO of DigitalBridge. Ganzi offers his latest thoughts on AI infrastructure in a podcast from Infrastructure Investor, which is worthwhile listening for anyone tracking data center growth. A few highlights: - Ganzi sees AI infrastructure as a 10-year undertaking that could add about 60 gigawatts of data center capacity. - Profitable "killer apps" may not emerge for several years. "With all of these tectonic shifts in technology, you have to have a bit of patience.” - Ganzi has long emphasized sustainability as a key priority, and believes water scarcity will demand more attention. "Most people don't understand what a crisis water can become in AI infrastructure." Lots more, including thoughts on the coming debate on shared investment on power and water infrastructure. Hat tip to Gordon Dolven for the link. https://lnkd.in/eiDEjBrd #ai #datacenter #digitalinfrastructure #investing #cloud #infrastructure

AI’s power surge, energy infrastructure merge to create electrifying investment opportunities Investors got some of the rate cuts they clamored for last year as #inflation moderated. But upside inflation risk — a potential byproduct of shifting fiscal, trade and regulatory policy under the new administration — makes it much less likely the Federal Reserve will lower rates again when it meets this week. Although U.S. economic #growth has so far proved resilient in the aftermath of the Fed’s aggressive 2022-2023 hiking cycle, financial #markets will focus on whether sticky inflation and a prevailing higher-for-longer interest rate environment (now that the Fed is poised to pause its easing path) will ultimately lead to a slowdown in the #economy. Where might investors want to allocate some of their portfolio dollars amid this uncertainty? One of our favored asset classes is publicly listed #infrastructure, which offers diversification advantages, provides a hedge against inflation via predictable cash flows and is currently benefiting from exponential growth in energy demand — particularly given the rapid evolution of artificial intelligence (#AI) and the corresponding need to power data centers. Despite speculation that Chinese AI startup DeepSeek AI may have the ability to compete effectively with today’s established AI leaders at a fraction of the development cost, capital expenditure (capex) trends, along with prevailing AI models and data center growth, still point to a massive — and compelling — long-term investment opportunity in infrastructure. For more detailed insights on surging global energy demand and allocating to publicly listed infrastructure, check out our latest CIO Weekly Commentary, “Investing in a power-hungry economy”: https://lnkd.in/gJKURdAk Would you consider adding publicly listed infrastructure investments to your portfolio?

I am truly excited to share the latest findings from The World Bank's Private Participation in Infrastructure (#PPI) report. While PPI dipped by 5% from 2022, investments were on par with the previous five-year average, with funding spreading across 68 countries and 322 projects. Noteworthy points: * Countries like Guinea Bissau, Libya, Papua New Guinea, São Tomé and Príncipe, and Suriname secured their first PPI transactions in over a decade; * Investments in renewable energy tripled, especially in the East Asia and Pacific region, underscoring a global commitment to sustainability; * Infrastructure investment has almost doubled in the Middle East and North Africa region; and * The world's poorest countries received an 18% increase in PPI across 53 projects. The PPI database offers critical insights into infrastructure investment trends, helping us identify opportunities to close the world's infrastructure finance gap. Read more about this year’s report: http://wrld.bg/FSbq50RG8mt