Big Tech's $1.2 Trillion Hyperscaler AI Bet Could Ignite the Next Semiconductor ETF Rally

Semiconductor stocks sold off on fears that Big Tech’s AI spending had peaked. Bank of America says the opposite is true: it now expects hyperscaler capex to top $1.2 trillion over the next 12 months, up from roughly $700 billion. Morgan Stanley agrees, projecting about $800 billion in 2026 and $1.2 trillion in 2027.

For ETF investors, the question is no longer whether AI spending is slowing, but which funds are positioned to benefit from it.

AI Spending Is Broadening Beyond GPUs

Bank of America identified nine Buy-rated semiconductor stocks with at least 30% upside, spanning compute, memory, networking and semiconductor equipment rather than concentrating solely on Nvidia Corp. (NASDAQ:NVDA).

The list includes Marvell Technology Inc. (NASDAQ:MRVL), Micron Technology Inc. (NASDAQ:MU), Nvidia, Broadcom Inc. (NASDAQ:AVGO), Advanced Micro Devices Inc. (NASDAQ:AMD), Credo Technology Group Holding Ltd. (NASDAQ:CRDO), Applied Materials Inc. (NASDAQ:AMAT), KLA Corp. (NASDAQ:KLAC) and Intel Corp. (NASDAQ:INTC).

That breadth reinforces the case for diversified semiconductor ETFs.

Broad Semiconductor ETFs Cover the Entire AI Supply Chain

• The VanEck Semiconductor ETF (NASDAQ:SMH) holds many of Bank of America’s highest-conviction names, including Nvidia, Broadcom, AMD, Micron, Applied Materials and KLA. Its market-cap-weighted portfolio gives investors concentrated exposure to AI leaders while also capturing equipment makers benefiting from rising fabrication spending.

• The iShares Semiconductor ETF (NASDAQ:SOXX) provides broader exposure across chip designers and equipment companies, making it well positioned if AI gains extend beyond mega-cap names.

• Meanwhile, the SPDR S&P Semiconductor ETF (NYSE:XSD) uses an equal-weighted methodology, giving greater exposure to mid-cap semiconductor companies that could benefit if the AI rally broadens.

Memory and Equipment Remain Key AI Bottlenecks

Micron, with 88% implied upside in Bank of America’s estimates, highlights memory as one of AI’s biggest supply constraints. That could support specialized funds such as the Roundhill Memory ETF (BATS:DRAM), which focuses on memory-chip manufacturers and related suppliers.

The fund has been one of this year’s standout AI-themed ETF launches as investors increasingly target the memory segment.

Bank of America’s bullish outlook also extends upstream. Applied Materials and KLA underscore that every additional AI accelerator requires more wafer fabrication, inspection and manufacturing capacity. Broad semiconductor ETFs such as SMH and SOXX already provide meaningful exposure to these equipment leaders.

The AI trade is no longer centered on GPUs alone.

Higher hyperscaler spending supports demand across memory, networking, chip equipment and manufacturing, reducing dependence on a single winner. Semiconductor ETFs already bundle those exposures into one portfolio.

Photo: Shutterstock