The hype around OpenAI’s $830 billion valuation has dominated headlines, yet beneath the surface lies a more compelling investment narrative. While household names like Alphabet and Microsoft have delivered impressive gains to shareholders, a quieter group of companies—those providing the essential backbone of AI infrastructure—are quietly generating superior returns. The real power of money in AI isn’t flowing to software developers; it’s flowing to those who build the physical and digital plumbing that makes AI possible.
Revenue Growth: When Infrastructure Outpaces Innovation
At first glance, the headline AI companies look unstoppable. Alphabet, the maker of Gemini and a major AI investor, has achieved 37.3% trailing-12-month revenue growth over three years. Microsoft, with its Copilot integration across products, posted an even more impressive 44% TTM revenue expansion during the same period. For companies of their scale, these numbers represent genuine strength.
Yet dig deeper into the AI supply chain, and a striking pattern emerges. Vertiv Holdings, which manufactures industrial cooling systems and electrical infrastructure for data centers, has grown TTM revenue by 70.4% over three years—a 93% premium over Microsoft’s rate. Arista Networks, the provider of networking switches and data center connectivity infrastructure, has absolutely crushed it with 92.8% TTM revenue growth, more than double Alphabet’s expansion rate.
This isn’t a fluke. The companies providing the foundational technology—power systems, cooling equipment, and networking infrastructure—have captured the essence of where AI buildout capital actually flows. These are the picks and shovels being used to construct the AI gold rush, and their growth tells the real story.
Profitability: The Gap Widens Dramatically
The divergence becomes even more pronounced when examining profit growth, revealing where the true power of money materializes.
Microsoft has expanded net income by 55.5% since December 2022, while Alphabet has more than doubled its profits with 107.2% growth. Impressive achievements for tech behemoths managing hundred-billion-dollar earnings bases.
But consider the infrastructure providers: Arista Networks has generated 148.2% net income growth, while Vertiv has delivered a staggering 1,250% expansion in net profits over the same three-year window. While Vertiv ($1 billion in net income) and Arista ($3.4 billion) operate at smaller absolute profit levels than Alphabet and Microsoft’s $100 billion-plus figures, the trajectory is unmistakable. Not only are infrastructure companies growing revenue faster, they’re translating that revenue into profits at an accelerated pace.
This profit acceleration reflects a critical market dynamic: as AI infrastructure becomes increasingly commodified and demand soars, operating leverage kicks in. Every incremental dollar of revenue drops much faster to the bottom line for Vertiv and Arista than it does for software-centric companies managing complex R&D expenses.
Market Recognition Drives Valuations Higher
The investment community has clearly recognized this disparity. Despite superior growth rates, Vertiv and Arista command premium valuations that reflect both current performance and future expectations.
On a forward price-to-earnings basis—accounting for near-term growth—Microsoft trades at 30x forward earnings while Alphabet sits at 29.7x. Standard valuations for mature AI leaders with global reach.
Compare this to Vertiv, trading at 40.6x forward earnings, and Arista, at 45.8x forward earnings. On trailing P/E multiples, the premium widens further: Vertiv at 63.2 and Arista at 50.2 far exceed Microsoft’s 34.7 and Alphabet’s 30.9.
The market’s verdict is clear: investors believe the infrastructure segment offers superior upside potential. The fact that networking equipment and cooling system manufacturers command higher valuations than the creators of Gemini and Copilot signals something profound about where the investment community expects the next wave of AI-driven value creation to originate.
Strategic Implications for Investors
The power of money follows infrastructure development in emerging technological paradigms. As AI infrastructure deployment accelerates and capital investments pour into data centers, the companies provisioning that infrastructure—rather than the software layered on top—are capturing disproportionate returns.
This doesn’t suggest avoiding Alphabet or Microsoft; both remain formidable technology leaders. Rather, it highlights an often-overlooked opportunity: the unglamorous but extraordinarily profitable business of enabling AI at scale. For investors seeking exposure to genuine AI infrastructure economics, Vertiv, Arista, and similar connectivity and cooling specialists deserve serious portfolio consideration, particularly during any market weakness that creates entry point opportunities.
The next generation of AI wealth may well be built not by those creating AI applications, but by those ensuring AI infrastructure can operate reliably, efficiently, and at global scale.
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Where the Real Power of Money Flows: AI Infrastructure Outperforms Software Giants
The Surprising Truth About AI Investment Returns
The hype around OpenAI’s $830 billion valuation has dominated headlines, yet beneath the surface lies a more compelling investment narrative. While household names like Alphabet and Microsoft have delivered impressive gains to shareholders, a quieter group of companies—those providing the essential backbone of AI infrastructure—are quietly generating superior returns. The real power of money in AI isn’t flowing to software developers; it’s flowing to those who build the physical and digital plumbing that makes AI possible.
Revenue Growth: When Infrastructure Outpaces Innovation
At first glance, the headline AI companies look unstoppable. Alphabet, the maker of Gemini and a major AI investor, has achieved 37.3% trailing-12-month revenue growth over three years. Microsoft, with its Copilot integration across products, posted an even more impressive 44% TTM revenue expansion during the same period. For companies of their scale, these numbers represent genuine strength.
Yet dig deeper into the AI supply chain, and a striking pattern emerges. Vertiv Holdings, which manufactures industrial cooling systems and electrical infrastructure for data centers, has grown TTM revenue by 70.4% over three years—a 93% premium over Microsoft’s rate. Arista Networks, the provider of networking switches and data center connectivity infrastructure, has absolutely crushed it with 92.8% TTM revenue growth, more than double Alphabet’s expansion rate.
This isn’t a fluke. The companies providing the foundational technology—power systems, cooling equipment, and networking infrastructure—have captured the essence of where AI buildout capital actually flows. These are the picks and shovels being used to construct the AI gold rush, and their growth tells the real story.
Profitability: The Gap Widens Dramatically
The divergence becomes even more pronounced when examining profit growth, revealing where the true power of money materializes.
Microsoft has expanded net income by 55.5% since December 2022, while Alphabet has more than doubled its profits with 107.2% growth. Impressive achievements for tech behemoths managing hundred-billion-dollar earnings bases.
But consider the infrastructure providers: Arista Networks has generated 148.2% net income growth, while Vertiv has delivered a staggering 1,250% expansion in net profits over the same three-year window. While Vertiv ($1 billion in net income) and Arista ($3.4 billion) operate at smaller absolute profit levels than Alphabet and Microsoft’s $100 billion-plus figures, the trajectory is unmistakable. Not only are infrastructure companies growing revenue faster, they’re translating that revenue into profits at an accelerated pace.
This profit acceleration reflects a critical market dynamic: as AI infrastructure becomes increasingly commodified and demand soars, operating leverage kicks in. Every incremental dollar of revenue drops much faster to the bottom line for Vertiv and Arista than it does for software-centric companies managing complex R&D expenses.
Market Recognition Drives Valuations Higher
The investment community has clearly recognized this disparity. Despite superior growth rates, Vertiv and Arista command premium valuations that reflect both current performance and future expectations.
On a forward price-to-earnings basis—accounting for near-term growth—Microsoft trades at 30x forward earnings while Alphabet sits at 29.7x. Standard valuations for mature AI leaders with global reach.
Compare this to Vertiv, trading at 40.6x forward earnings, and Arista, at 45.8x forward earnings. On trailing P/E multiples, the premium widens further: Vertiv at 63.2 and Arista at 50.2 far exceed Microsoft’s 34.7 and Alphabet’s 30.9.
The market’s verdict is clear: investors believe the infrastructure segment offers superior upside potential. The fact that networking equipment and cooling system manufacturers command higher valuations than the creators of Gemini and Copilot signals something profound about where the investment community expects the next wave of AI-driven value creation to originate.
Strategic Implications for Investors
The power of money follows infrastructure development in emerging technological paradigms. As AI infrastructure deployment accelerates and capital investments pour into data centers, the companies provisioning that infrastructure—rather than the software layered on top—are capturing disproportionate returns.
This doesn’t suggest avoiding Alphabet or Microsoft; both remain formidable technology leaders. Rather, it highlights an often-overlooked opportunity: the unglamorous but extraordinarily profitable business of enabling AI at scale. For investors seeking exposure to genuine AI infrastructure economics, Vertiv, Arista, and similar connectivity and cooling specialists deserve serious portfolio consideration, particularly during any market weakness that creates entry point opportunities.
The next generation of AI wealth may well be built not by those creating AI applications, but by those ensuring AI infrastructure can operate reliably, efficiently, and at global scale.