The explosive growth of artificial intelligence is creating an unprecedented crisis: data centers are running out of power and cooling capacity faster than electricity grids can keep up. While headlines focus on chip shortages and AI model breakthroughs, the real constraint emerging in 2026 is the unglamorous but critical infrastructure needed to keep these power-hungry systems running without melting down.

Why Is Data Center Power Consumption Becoming the Limiting Factor?

Generative AI systems like ChatGPT consume roughly 10 times more energy than traditional Google searches, and large AI data centers can guzzle as much power as mid-sized cities. This energy appetite is forcing hyperscalers and enterprises to pour hundreds of billions into infrastructure that most people never see: cooling systems, electrical construction, power distribution networks, and energy management technologies.

The numbers are staggering. Hyperscalers alone are projected to spend roughly $700 billion or more in AI-related capital expenditures in 2026, with spending ramping up again in 2027 after $400 billion in 2025. Globally, companies will pour $7 trillion into data center capital expenditures by 2030, with $1.3 trillion specifically aimed at energy infrastructure. Meanwhile, the U.S. electricity grid was already desperate for investment before the AI boom pushed it to the brink, especially in AI data center hubs.

Which Companies Are Profiting From the Infrastructure Boom?

Two infrastructure stocks have emerged as major beneficiaries of this spending spree: Vertiv Holdings (VRT) and EMCOR Group (EME). Both companies are classified as "picks-and-shovels" AI stocks, meaning they profit from the infrastructure buildout regardless of which AI models or technologies ultimately dominate the market.

Vertiv, based in Columbus, Ohio, provides critical digital infrastructure technologies that help AI data centers run as efficiently as possible around the clock. The company has experienced remarkable growth, doubling its revenue between 2021 and 2025 and growing its earnings per share from $0.33 to $3.41 over the same period. The stock has soared approximately 1,050% in the past three years, significantly outpacing Nvidia's 360% gain, and earned a spot in the S&P 500 in March 2026.

Vertiv's core competitive advantage lies in solving a specific technical challenge: cutting-edge AI systems pack so many high-power graphics processing units (GPUs) into dense racks that traditional air cooling can no longer keep up. The company's advanced liquid cooling portfolio has become essential to prevent overheating and maintain performance. Vertiv is actively expanding its manufacturing footprint to support growing customer demand for AI and high-density computing applications, and it is even working with Nvidia to help solve AI cooling challenges.

EMCOR Group, meanwhile, is a standout provider of mechanical and electrical construction services, industrial and energy infrastructure, and building services. The company handles everything from constructing hyperscale data centers to providing 24/7 support for cutting-edge facilities and implementing energy efficiency technologies. EMCOR's growth has skyrocketed over the last five years, with earnings per share jumping from $7.06 in 2021 to $28.19 in 2025.

What Are the Growth Projections for These Infrastructure Companies?

Both Vertiv and EMCOR are positioned for sustained growth as AI infrastructure spending accelerates. Vertiv is projected to grow its adjusted earnings per share by 52% in 2026 and 34% in 2027, effectively doubling its 2025 total. The company is expected to grow its revenue by 34% in 2026 and 28% in 2027, reaching $17.64 billion and doubling 2024's total.

EMCOR's adjusted earnings are projected to climb 14% in 2026 and 12% in 2027, on 12% and 8% respective sales growth. The company boasts a strong balance sheet with near-zero debt, and its shareholders' equity is soaring. Both stocks have pulled back from their peaks and are finding support heading into their second quarter earnings releases, with Vertiv set to report on July 29 and EMCOR on July 30.

How to Evaluate Data Center Infrastructure Investments

• Earnings Growth Trajectory: Look for companies projecting double-digit earnings growth in 2026 and 2027, as this indicates sustained demand from hyperscalers and enterprises building out AI infrastructure.
• Revenue Diversification: Prioritize companies that are "AI agnostic," meaning they profit from infrastructure buildout regardless of which AI models or technologies ultimately dominate the market.
• Manufacturing Expansion: Companies actively expanding their manufacturing footprint to support growing customer demand for AI and high-density computing are better positioned to capture market share as demand accelerates.
• Technical Specialization: Seek out companies solving specific technical bottlenecks, such as advanced liquid cooling systems or electrical construction services, that are essential to keeping AI data centers operational.
• Balance Sheet Strength: Companies with strong balance sheets and minimal debt are better positioned to fund the capital expenditures required to scale manufacturing and service delivery.

Could Quantum Computing Offer an Alternative Path to Lower Energy Consumption?

While traditional infrastructure companies are racing to build cooling and power systems for classical AI data centers, an emerging alternative is gaining attention: quantum computing. IonQ and research partner QuantumBasel recently released findings showing that quantum systems could cut AI energy consumption significantly at scale.

The research identifies a critical crossover point at approximately 34 qubits, where quantum computing methods consume less energy than classical GPU-based approaches for comparable AI tasks. If quantum hardware can reliably handle AI workloads with lower energy consumption at scales around or beyond 34 qubits, quantum computing could emerge as a meaningful participant in sustainable computing conversations.

However, quantum computing remains in early stages of commercialization. IonQ's stock has declined 40.5% over the past 30 days and 25.8% year to date, despite a five-year return of 249.2%. Earnings are projected to decline by an average of 45.9% per year over the next three years, highlighting the gap between promising research and commercial viability. Analyst price targets for IonQ currently range from $44.78 to $100.00, reflecting genuine uncertainty about how quickly the company's quantum technology can translate into enterprise adoption.

What Does This Mean for the AI Industry's Future?

The infrastructure bottleneck represents a fundamental shift in how the AI industry will evolve. While chip makers like Nvidia have captured most of the headlines and investor attention, the companies building the physical systems to support AI are becoming equally critical to the industry's growth. U.S. electricity demand is projected to increase 25% by 2030 and approximately 100% by 2050, driven by AI growth, reshoring of critical manufacturing such as semiconductors, electrification, and other factors.

This creates a powerful multi-year tailwind for companies that supply energy, chips, cooling systems, construction services, and other infrastructure components. The market is recognizing this shift, with infrastructure stocks like Vertiv and EMCOR significantly outperforming traditional AI chip makers over the past three to five years. As hyperscalers continue to pour hundreds of billions into power-hungry infrastructure, the unsexy but essential work of keeping data centers cool and powered will likely remain one of the most profitable segments of the AI boom.