The real opportunity in artificial intelligence isn't just about the chips that power AI systems; it's about the overlooked companies building the infrastructure that makes those systems actually work in the real world. While NVIDIA remains the world's chief supplier of artificial intelligence data center processors, a handful of under-the-radar companies are solving critical problems that AI platforms depend on to operate reliably and efficiently.

What Infrastructure Do AI Systems Actually Need Beyond Processing Power?

Building a powerful AI platform is one challenge. Making it do something useful in the real world is entirely another. AI systems need more than just processing power; they require a complete ecosystem of sensors, controllers, and connectivity solutions that convert physical information into digital data and then execute mechanical actions based on that data.

ON Semiconductor exemplifies this principle. The company manufactures industrial sensors, wireless antennas, microcontrollers, power controllers, and motor controllers used in everything from driver-assistance technology to factory automation to medical diagnostic equipment. ON is currently partnering with electric vehicle makers Geely and Nio, and has even collaborated with NVIDIA to develop new 800-volt power solutions for next-generation AI data centers designed to improve power efficiency.

The industrial world is becoming increasingly automated across factories, automobiles, healthcare, and even cities. This expansion creates demand for companies that can provide comprehensive solutions rather than just individual components. ON Semiconductor represents a consistent, profitable grower in this space, even as it remains relatively unknown compared to household names like NVIDIA.

How to Identify the Critical Infrastructure Players in AI?

• Sensor and Control Integration: Look for companies that provide industrial sensors, wireless antennas, and microcontrollers that enable AI-powered systems to perceive and respond to their environment in real time.
• Power Management Solutions: AI data centers and automated systems require sophisticated power controllers and high-capacity semiconductors to manage energy efficiently, especially as systems become more complex and demanding.
• Data Center Interconnection: Companies that solve interconnection problems within AI data centers, such as retimers, fabric switches, and memory controllers, are essential to processing the massive amounts of data modern AI systems generate.

Another critical player is Astera Labs, which designs and manufactures systems that interconnect an AI data center's thousands of processors. While NVIDIA provides the graphics processing units (GPUs) that power AI development, Astera's Aries retimers and cables receive and deliver high-speed signals from processors. Its Scorpio fabric switches maximize available bandwidth, while its Leo memory controllers improve the existing memory capacity of legacy physical interfaces.

Astera Labs also offers software that makes all of this hardware work together to achieve optimization. The company's customer list includes hyperscalers like Microsoft and Amazon. Last fiscal quarter's revenue of $308.4 million was 93% higher year over year, with analysts expecting comparable revenue growth this year and next.

Why Are Investors Overlooking These Companies?

The problem with stepping into well-known names like NVIDIA is that these trades can become very crowded and therefore very expensive. As legendary investor Warren Buffett famously advised, "You can't buy what is popular and do well." While NVIDIA and other household names have continued rallying even after becoming widely recognized must-haves, many investors suspect that these stocks' highest-growth phase is in the rearview mirror.

Smart investors are looking for the next unknown AI gem that's yet to be discovered and subsequently fully valued. Companies like ON Semiconductor and Astera Labs operate in spaces where the underlying demand is accelerating, yet they remain largely unknown outside of industry circles. ON Semiconductor's revenue and earnings growth are apt to accelerate in the foreseeable future, driven by its comprehensive offerings at a time when factories, automobiles, healthcare, and cities are becoming more AI-automated.

Astera Labs is particularly positioned for growth. Industry research firm Global Market Insights expects the worldwide data center infrastructure market that Astera serves to grow at an average annual pace of 13.4% through 2034. The company is already profitable, on pace to report nearly $3 per-share profit in 2026, en-route to an expected $4.33 for 2027.

The AI revolution depends on NVIDIA's processing power, but it equally depends on the companies building sensors, power management systems, and data center infrastructure. As AI technology moves from research labs into real-world deployment across industries, the demand for these supporting technologies will only intensify. The companies providing them may offer investors a more compelling opportunity than the already-crowded NVIDIA trade.