For many investors, Nvidia stock has become almost synonymous with the artificial intelligence boom. That is hardly surprising. Nvidia reported record revenue of $81.6 billion for the first quarter of fiscal 2027, up 85% from a year earlier, while its Data Center revenue reached $75.2 billion, up 92% year over year. In other words, demand for AI chips remains the central story of the market.
But the AI trade is no longer only about one chipmaker. Every new AI model, chatbot, enterprise tool or cloud platform needs far more than graphics processing units. It needs power, cooling, high-speed networking, optical components, advanced servers, data-center construction and energy infrastructure. That is why investors are increasingly looking beyond Nvidia stock and asking a broader question: which lesser-known equities are quietly riding the same wave?
The AI boom is becoming an infrastructure boom
The next phase of the AI market is being shaped by capital expenditure. Major technology companies are spending hundreds of billions of dollars to build data centers capable of training and running artificial intelligence models. According to Reuters, an analysis by Bridgewater Associates estimated that Alphabet, Amazon, Meta and Microsoft could invest about $650 billion in AI infrastructure in 2026.
That kind of spending creates a much wider investment map. If Nvidia supplies the most visible engine of the AI revolution, companies around the data center supply chain are providing the cooling systems, networking equipment, power infrastructure and manufacturing capacity that make the AI boom physically possible.
Read also: Sustainable investments 2026: JYP Entertainment and Nvidia among the favorites
Vertiv: cooling the AI data center
One of the most direct examples is Vertiv Holdings. The company specializes in critical digital infrastructure, including power management and cooling systems for data centers. This is becoming more important as AI servers run hotter and consume more electricity than traditional computing workloads.
Vertiv’s latest numbers show why the company has become one of the clearest infrastructure plays linked to AI. The company reported first-quarter 2026 net sales of $2.65 billion, up 30% from the same period a year earlier, and adjusted diluted earnings per share rose 83%.
For investors, Vertiv is not a chip stock in the classic sense. It is a “picks and shovels” company for the data-center economy. The opportunity is clear: more AI servers mean more cooling, more power systems and more resilient infrastructure. The risk is also clear: after a strong run, valuations already reflect high expectations, so any slowdown in data-center orders could hit the stock hard.
Astera Labs: the connectivity layer inside AI systems
Another name that has attracted attention is Astera Labs. The company makes semiconductor-based connectivity products used in AI and cloud infrastructure, including technologies built around PCIe, CXL, Ethernet and other high-speed standards.
Astera Labs reported first-quarter 2026 revenue of $308.4 million, up 93% year over year and 14% sequentially. The company also said its PCIe 6 AI fabric and signal conditioning portfolio delivered strong growth during the quarter.
The investment case is easy to understand. AI chips are powerful, but they need to move huge amounts of data quickly between processors, memory, switches and servers. That makes connectivity a bottleneck — and a potential profit pool. Astera Labs is therefore a more specialized way to invest in AI infrastructure beyond Nvidia stock. However, it is also a high-growth, high-valuation stock, which makes it vulnerable if investor enthusiasm cools.
Credo Technology: cables, speed and AI networking
Credo Technology is another smaller company benefiting from the AI networking boom. It focuses on high-speed connectivity solutions, including products designed to move data efficiently inside large-scale data centers.
The company reported fourth-quarter fiscal 2026 revenue of $437 million, up 157% year over year. Credo also reported non-GAAP diluted earnings per share of $1.16 and ended the quarter with $1.4 billion in cash and short-term investments.
Credo’s appeal lies in a simple but powerful trend: AI data centers are not just clusters of chips; they are massive communication systems. As workloads become larger and more complex, the need for fast, energy-efficient connections rises. That gives companies like Credo a strategic role in the AI supply chain.
Read also: US stocks rose slightly as the market continues to monitor developments in the Middle East
Celestica: the less glamorous side of AI hardware
Not every AI winner needs to be a famous semiconductor company. Celestica, a Canadian electronics manufacturing and supply-chain company, is a good example of a less glamorous but important AI infrastructure beneficiary.
The company reported first-quarter 2026 revenue of $4.05 billion and adjusted earnings per share of $2.16. Its management pointed to strong performance in its Connectivity & Cloud Solutions business, which is closely tied to hyperscaler, networking and cloud infrastructure demand.
Celestica sits in the part of the market where AI demand becomes physical hardware: systems, networking equipment, integration and manufacturing. For investors looking beyond Nvidia stock, this type of company can offer exposure to AI infrastructure without relying purely on GPU pricing. But it also carries classic manufacturing risks, including margins, execution pressure and dependence on large customers.
Coherent and Fabrinet: the optical backbone of AI
AI data centers also need optical technologies to move information at extremely high speeds. That has brought companies such as Coherent and Fabrinet into focus.
Coherent reported third-quarter fiscal 2026 revenue of $1.81 billion, with non-GAAP earnings per diluted share of $1.41. The company is active in photonics, lasers and optical communications — technologies that matter as AI systems require faster and more efficient data transmission.
Fabrinet, meanwhile, reported third-quarter fiscal 2026 revenue of $1.21 billion, compared with $871.8 million a year earlier. The company manufactures optical communications and precision components, giving it exposure to the data-center and telecom equipment cycle.
These companies are not as widely discussed as Nvidia, but they operate in a crucial part of the AI ecosystem. If AI workloads keep growing, data needs to move faster across chips, racks and data centers. That makes optical components and advanced manufacturing an important part of the broader AI investment theme.
Arista Networks: AI needs switches, not just chips
Arista Networks is better known than some of the smaller names on this list, but it still receives less mainstream attention than the mega-cap AI leaders. The company makes cloud networking equipment, including high-performance Ethernet switching used by major cloud providers.
In the first quarter of 2026, Arista reported revenue of $2.709 billion, up 35.1% from the first quarter of 2025. The company also continues to position itself as a key supplier of networking infrastructure for large AI and cloud environments.
Arista’s role is important because AI data centers depend on networking performance. GPUs may get the headlines, but slow or inefficient networking can limit the performance of the entire cluster. For investors, Arista represents a more established way to participate in AI infrastructure, although its size and valuation mean it is no longer a hidden opportunity.
Energy and power infrastructure: the AI boom’s physical limit
The most overlooked AI trade may be electricity. AI data centers need vast amounts of reliable power, and that has pushed investors toward utilities, grid operators and power-equipment companies. Reuters reported that BlackRock’s 2026 survey found investors increasingly favored energy and infrastructure providers over traditional big tech as a way to play the AI theme.
This is where names such as GE Vernova, Vistra or Constellation Energy enter the conversation. They are not AI companies in the narrow sense, but they may benefit if data centers continue to increase electricity demand. GE Vernova, for example, raised its 2026 outlook as AI-driven data-center demand supported power equipment orders.
The logic is simple: AI cannot scale without power. According to the International Energy Agency, data centers consumed about 415 terawatt-hours of electricity in 2024, or roughly 1.5% of global electricity consumption. If AI adoption keeps accelerating, the power side of the story may become just as important as the chip side.
The opportunity — and the risk
The case for looking beyond Nvidia stock is strong. AI infrastructure is a broad ecosystem, and many companies outside the spotlight are already reporting rapid growth. Cooling providers, connectivity specialists, optical manufacturers, server builders and energy companies all have a role to play.
But investors should be careful. Many AI-linked equities have already priced in years of growth. Some trade at high earnings multiples, and many depend on a small number of hyperscale customers. If cloud companies slow their spending, delay projects or demand lower prices, the impact could spread quickly through the supply chain.
The key lesson is that the AI boom is real, but not every AI-related stock is automatically cheap or safe. Nvidia stock remains the symbol of the market’s excitement, yet the next stage of the story may be decided by less famous companies building the infrastructure around it. For investors, that makes the AI trade broader, more interesting — and potentially more dangerous.
