The race to power artificial intelligence is reshaping which companies investors should watch, and the winners aren't just chip makers. With major hyperscalers committing $750 billion to AI infrastructure spending in 2026, a new class of dividend-paying utilities and infrastructure firms is emerging as the backbone of this expansion, handling everything from cooling systems to grid upgrades to large-scale project delivery.

Why Are Infrastructure Companies Suddenly Central to AI's Growth?

The AI data center boom has created an unexpected opportunity for companies that operate far behind the scenes. While semiconductor firms grab headlines, the real infrastructure challenge lies in keeping these massive computing facilities running reliably and efficiently. Hyperscalers are investing heavily in cooling systems, power management, and grid resilience, creating demand for specialized equipment and expertise that goes well beyond chips.

This shift reflects a fundamental reality: AI data centers consume enormous amounts of power and generate intense heat. A single facility can draw as much electricity as a small city, requiring sophisticated cooling, monitoring, and control systems. Companies that provide these solutions are now positioned to capture a significant share of the $750 billion infrastructure budget.

Which Companies Are Positioned to Benefit Most?

Three dividend-paying infrastructure firms stand out as particularly well-positioned for this wave of investment. Each operates in a different segment of the AI infrastructure ecosystem, but all share exposure to the same underlying trend: hyperscalers' urgent need to build out reliable, efficient data center capacity.

• Emerson Electric (NYSE: EMR): A global technology company with a $79.3 billion market cap that provides sensors, valves, control systems, and automation software to utilities and industrial operators. The company generates most revenue from intelligent devices like sensors ($4.2 billion), safety and productivity solutions ($1.4 billion), and software and test equipment ($1.6 billion). Emerson is pushing into industrial AI through tools like Nigel AI and AspenTech's grid software, positioning it to help utilities and data center operators manage higher power demands and reliability requirements.
• AECOM (NYSE: ACM): A global infrastructure consulting firm with an $8.9 billion market cap that helps governments and businesses plan, design, and deliver large projects across transportation, water, energy, and environmental sectors. AECOM generates roughly $12.4 billion in revenue from the Americas and $3.6 billion internationally. The company is winning contracts with major hyperscalers on power, water, and security projects while rolling out its own AI tools to improve efficiency on client engagements.
• Carrier Global (NYSE: CARR): A large HVAC and refrigeration company with a $58.2 billion market cap that provides heating, cooling, ventilation, and energy management systems globally. Carrier generates revenue primarily from Climate Solutions Americas ($10.4 billion), Europe ($5.2 billion), Asia Pacific and Middle East/Africa ($3.3 billion), and Transportation ($3.0 billion). The company sits at the intersection of AI data center expansion and climate efficiency demands, offering AI-enabled platforms like Abound and Lynx that use sensor data to anticipate failures and improve energy efficiency.

What Makes These Companies Different From Traditional Tech Plays?

The appeal of these infrastructure firms lies in their combination of growth exposure and income stability. Unlike pure-play AI chip companies, which can be volatile, these firms offer regular dividend payments alongside exposure to the AI infrastructure buildout. They also benefit from what investors call "balance sheet resilience," meaning they have strong financial foundations to weather economic uncertainty.

Emerson Electric exemplifies this balance. The company combines a long history of dividend payments with what analysts describe as high-quality earnings, expanding profit margins, and a growing backlog tied to power, liquefied natural gas (LNG), and life sciences projects. Its push into industrial AI through grid software adds a forward-looking growth angle to its traditional infrastructure business.

AECOM offers direct exposure to AI-driven data center buildouts alongside climate resilience projects and government-backed infrastructure work. The company is building a record backlog of higher-margin consulting work, particularly as hyperscalers and governments compete to secure reliable power and water resources for their facilities.

Carrier Global sits at a unique intersection. As hyperscalers invest heavily in cooling to handle the intense heat generated by AI chips, Carrier's HVAC and refrigeration expertise becomes critical. The company's AI-enabled monitoring platforms help data center operators optimize energy use, directly addressing the efficiency demands that come with massive power consumption.

How to Identify AI Infrastructure Investment Opportunities?

For investors seeking exposure to AI's infrastructure boom without the volatility of chip stocks, a systematic approach can help identify the most promising opportunities:

• Track Backlog Growth: Look for companies with expanding project backlogs tied to power, energy, and data center infrastructure. A growing backlog signals that hyperscalers and governments are committing real capital to these projects, not just making announcements.
• Assess Dividend History and Resilience: Companies with long histories of stable or growing dividend payments demonstrate financial discipline and cash generation. This matters because infrastructure projects often take years to complete, requiring companies to maintain cash flow through market cycles.
• Evaluate Exposure to Multiple Catalysts: The strongest infrastructure plays benefit from multiple growth drivers simultaneously. For example, companies winning work with hyperscalers on data centers, with governments on grid upgrades, and with industrial customers on efficiency projects have more diversified revenue streams and lower execution risk.

What Are the Key Risks to Watch?

Despite the compelling opportunity, these infrastructure plays carry meaningful risks that investors must weigh carefully. High debt levels, reliance on public funding, and exposure to cyclical capital spending patterns all matter. Additionally, complex software integration and long-duration project timelines mean that execution quality directly affects returns.

Emerson Electric, for instance, faces high debt and insider selling activity, signaling that some company insiders may have concerns about valuation or near-term prospects. AECOM's heavy reliance on public funding means that changes in government spending priorities could impact its backlog. Carrier Global's debt coverage and regional demand variations require careful monitoring.

The broader lesson is clear: as AI infrastructure spending accelerates, the companies that build and maintain the physical systems supporting data centers are becoming as important as the chip makers themselves. For dividend-focused investors seeking exposure to this trend, infrastructure firms offer a compelling alternative to the volatility of pure-play AI stocks, provided they carefully assess each company's execution track record and financial resilience.