Five stocks riding AI's supply chain shocks

As Big Tech spends trillions on data centers, bottlenecks in power, fiber, memory, and chips are creating temporary pricing power for suppliers.

Sep 24, 2026

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Five stocks riding AI's supply chain shocks

As Big Tech spends trillions on data centers, bottlenecks in power, fiber, memory, and chips are creating temporary pricing power for suppliers.

In brief

As Big Tech spends trillions on data centers, bottlenecks in power, fiber, memory, and chips are creating temporary pricing power for suppliers. AI infrastructure spending will reach $31.6 trillion through 2050, creating a series of supply bottlenecks that reward different suppliers in sequence. Buy into these shocks…

The AI spending explosion

digital image of a blue background with a line stair-stepping higher and circles and the letters "AI" spread across the line to signal AI growth

Big Tech's combined capital spending on data centers jumped from $142 billion in 2022 to around $600 billion this year. Alphabet, Microsoft, Amazon and Meta alone will spend $5.3 trillion on capital expenditures between 2025 and 2030.

Decades of underbuilt capacity

The US share of global semiconductor manufacturing collapsed from 37% in 1990 to 12% by 2020. Over three decades, America outsourced power generation, manufacturing, packaging, and precision optics capacity to other countries.

Demand shocks move through supply chain

When trillions in fresh demand meets decades of underbuilt capacity, bottlenecks move sequentially through the supply chain. Each bottleneck temporarily gives pricing power to whichever supplier sits in it.

GPU bottleneck already passed

GPU bottleneck already passed

Nvidia's data center revenue hit $194 billion, up 68% year-over-year, with gross margins above 75%. The shock then moved to server assemblers like Dell and Super Micro.

Power is the current bottleneck

Constellation Energy signed long-term contracts at $30 to $40 above regional electricity rates, with adjusted earnings up 25% last quarter. AI data centers need gigawatts of new capacity that take years to build.

Memory is next in line

Micron's high-bandwidth memory is sold out through year-end, with gross margins rocketing to 85% from below 40% a year ago. Samsung and SK Hynix expect the memory shortage to persist into 2027 or later.

Optical connectivity emerging

Optical connectivity emerging

The shock is now moving into optical connectivity and specialized chips that shuttle data between GPUs inside server racks. This bottleneck is just getting started.

Spending will keep rising

Unlike prior infrastructure booms, AI data center spending requires equipment replacement every four to six years indefinitely. PwC projects annual spending climbing from $800 billion this year to $1.8 trillion by mid-century.

GE Vernova: power equipment maker

GE Vernova logo on smartphone with ticker board in the background

GE Vernova makes gas turbines and grid equipment utilities need to add power capacity. Power segment orders jumped 134% and Electrification orders up 66%, with order backlog expected to cross $200 billion by end of 2027.

“Microsoft has already lined up seven of the company's gas turbines for a Texas data center project alongside Chevron.”

Corning: fiber optic supplier

Corning invents more fiber-optic cable than any company on Earth. AI data center sales nearly doubled last quarter, and the company locked in a $6 billion multiyear deal to wire Meta's next-generation AI data centers.

Micron: memory chip leader

outside of micron technology headquarters in boise, idaho

Micron's quarterly revenue hit $41.5 billion, up 346% year-over-year, with gross margin at nearly 85%. High-bandwidth memory capacity is sold out through year-end and the shortage is expected to persist into 2027.

“No sector illustrates "sell everything you make at whatever price you want" better than memory chips right now.”

Nebius: GPU rental platform

Nebius rents GPU clusters to companies that need them, a model Wall Street calls a neocloud. Revenue jumped 454% to $582 million last quarter, and Nvidia invested $2 billion directly into the company.

“The constraint isn't finding customers, it's building fast enough to keep up with them.”

Astera Labs: chip interconnect

Astera Labs makes chips that connect GPUs inside server racks as they pack in more capacity. Quarterly revenue hit $392.4 million, up 104%, and management guided next quarter 30% above analyst expectations.

Valuations already reflect good times

Golden dollar signs falling on the blue background.

All five stocks have already had big runs and trade at valuations assuming no hiccups. Micron, Nebius and GE Vernova are particularly exposed to this risk if spending slows.

Buy in stages, not all at once

The case for owning these names is that $31.6 trillion in AI spending over 25 years is nowhere near finished. Each new leg of buildout crowns a fresh winner, but demand shocks eventually resolve as new supply comes online.

Own stocks while imbalance favors suppliers

Buy in stages rather than all at once, keep position sizes reasonable given volatility, and remember that demand shocks resolve as new supply gets built. The goal is to own these while the imbalance still works in their favor.

What it means

AI infrastructure spending will reach $31.6 trillion through 2050, creating a series of supply bottlenecks that reward different suppliers in sequence. Buy into these shocks while imbalances favor suppliers, not after they resolve.

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