These 7 Stocks Will Solve AI’s Most Important Bottleneck

Artificial intelligence has no shortage of obstacles. The industry is scrambling to secure enough electricity to power new data centers, enough land to build them, and enough high-bandwidth memory (HBM) to keep next-generation chips fed with data. 

Yet another constraint is emerging that could prove just as important: moving information between those chips fast enough to keep them working. As AI clusters grow from thousands to hundreds of thousands of GPUs, the network connecting them is becoming just as valuable as the processors themselves. 

For investors, that shifts attention beyond Nvidia (NASDAQ:NVDA | NVDA Price Prediction) and toward the companies building AI’s digital highways.

AI Needs Better Roads, Not Just Faster Cars

Intel (NASDAQ:INTC) CEO Lip-Bu Tan said on the No Priors podcast that the best investment opportunities lie where technology runs into a bottleneck. Today, one of the clearest choke points is interconnect technology — the hardware that transfers data between GPUs, CPUs, storage, and memory throughout an AI data center.

A modern AI cluster is really a massive logistics hub. GPUs perform the calculations, but every result depends on data arriving exactly when it is needed. If information is delayed, expensive processors sit idle. That wastes electricity, computing capacity, and billions of dollars of infrastructure investment.

The problem grows with scale. Traditional copper connections struggle to carry ever-faster electrical signals over longer distances because heat rises, power consumption increases, and signal quality deteriorates. Fiber optics solves many of those limitations by transmitting data as pulses of light instead of electricity, allowing far greater bandwidth while consuming less power.

Seven Companies Building AI’s Connectivity Infrastructure

Surprisingly, none of these companies manufactures the AI processors grabbing headlines. Instead, they build the infrastructure that allows those processors to work together efficiently.

Connectivity Could Become AI’s Next Arms Race

Every billion dollars a hyperscaler spends on GPUs creates additional demand for networking switches, optical modules, fiber, lasers, cables, and connectivity chips. Compute power alone no longer determines AI performance. The speed at which thousands of processors exchange information increasingly defines how much useful work those processors can perform.

That helps explain why Nvidia has aggressively expanded into photonics and optical networking through investments and strategic partnerships. CEO Jensen Huang also emphasized during Computex 2026 that while copper remains effective over shorter distances, optics become essential as AI systems scale across larger data centers.

Granted, these companies carry risks. Many rely heavily on a handful of hyperscale customers, and spending cycles can fluctuate from quarter to quarter. Valuations across AI infrastructure also remain elevated after a powerful multiyear rally.

Still, the long-term trend appears difficult to ignore. Industry spending is expanding beyond chips into every layer supporting AI infrastructure.

Key Takeaway

In short, AI’s next breakthrough may not come from building a faster GPU but from ensuring thousands of them can communicate without delay. Investors have spent the past three years focusing almost exclusively on semiconductor designers. The next phase of the AI buildout broadens the opportunity to companies enabling high-speed connectivity. 

Credo Semiconductor and Astera Labs offer the purest exposure to the networking bottleneck, while Marvell, Coherent, Lumentum, Corning, and Ciena provide investors with different ways to participate in what could become one of AI’s fastest-growing infrastructure markets. 

Ultimately, as AI clusters continue expanding, the companies building the digital roads between processors may prove every bit as indispensable as those building the processors themselves.