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EXCLUSIVE: Why The AI ETFs Trade Is Entering A More Difficult Phase

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EXCLUSIVE: Why The AI ETFs Trade Is Entering A More Difficult Phase

After two years of strong inflows, AI-focused exchange-traded funds (ETFs) are entering a tougher phase. Broad exposure that once amplified gains is now leaving investors concentrated in a small group of dominant tech stocks.

Jack Fu, chief executive of Draco Evolution, says many AI ETFs are still built for excitement, not durability.

“A lot of investors think they're buying diversified AI exposure,” Fu told Benzinga. But in many cases, they’re buying the same few big tech stocks in different wrappers, he explained.

Concentration Helped, But It Raises The Stakes

Billions of dollars have flowed into U.S.-listed technology and thematic ETFs over the past two years, as investors chose exposure to the AI theme in a single trade, removing the need to pick individual winners.

Most AI ETFs are heavily weighted toward a small group of mega-cap technology companies. That concentration helped drive strong returns as AI enthusiasm surged.

In fact, those companies have the cash, scale, and computing power to stay ahead, and they are often the first to turn AI spending into revenue, Fu noted.

But the flip side is risk. When a handful of stocks dominate a fund, any stumble from earnings misses, regulation, or valuation pressure can have an outsized impact on returns.

For instance, Global X Artificial Intelligence & Technology ETF (NASDAQ:AIQ), Roundhill Generative AI & Technology ETF (NYSE:CHAT) and Dan Ives Wedbush AI Revolution ETF (NYSE:IVES) have heavy exposure to the “Magnificient 7” stocks, particularly Nvidia Corp.(NASDAQ:NVDA), Alphabet (NASDAQ:GOOG) (NASDAQ:GOOGL) and Microsoft (NASDAQ:MSFT) alongside other chip stocks like Taiwan Semiconductor Manufacturing Co. (NYSE:TSM) and Micron Technology (NASDAQ:MU).

On the other hand, Draco’s AI ETF (NYSE:DRAI) has a more diversified, multi-asset base with major holdings in First American Funds Inc X Government Obligations Fund (NASDAQ:FGXXX) and other debt funds, as well as ETFs like the tech-heavy ProShares UltraPro QQQ (NASDAQ:TQQQ) and Direxion Daily S&P 500 Bull 3x Shares (NYSE:SPXL).

Over the past year, it rose by over 30%, as per data from Benzinga Pro.

Why The Structure Of AI ETFs Matters Now

Fu believes the next phase of AI investing will test how these funds are built. Many AI ETFs simply track companies linked to AI, without adjusting for market conditions or risk.

Over the past year, fixed income exposure in mixed-asset AI funds largely played a stabilising role, helping portfolios remain invested during bouts of volatility rather than forcing investors to reduce risk at inopportune times, Fu explained.

But as stock prices move in different directions and market conditions grow less predictable, Fu expects static AI ETFs to face more strain.

Attention and concentration will move toward the networking, power, and grid equipment sectors, along with firms that use AI to drive “measurable productivity.”

"AI is still a powerful long-term trend,” Fu said. But managing risk around that trend will “increasingly determine outcomes.”

This could push investors toward AI ETFs that are more flexible— adjusting exposure rather than holding every stock with an AI label.

And as investors become more cautious, simply owning an “AI ETF” may no longer be enough.

DRAI offers one example of that flexibility. Unlike most AI ETFs, it is not fully equity-only. During April’s tariff headlines and the tech selloff late last year, the fund reduced equity exposure and shifted toward defensive assets such as Treasuries, bonds, gold, and the U.S. dollar, helping offset some of the impact from broader market swings.

One Number Investors Should Watch Closely

If there is one signal that could quickly change the outlook for AI ETFs, Fu points to spending plans from the largest cloud and technology companies.

As long as those companies keep investing heavily, the broader AI ecosystem remains supported. But if spending slows for several quarters, expectations could reset quickly.

“The money going into chips and data centers is still massive,” Fu said. “But the market will care more about return on that spend, not just the headlines,” he added.

The comments come as Big Tech is ramping up AI investment at an unprecedented scale, with the “Magnificent 7” expected to pour nearly $400 billion this year into AI infrastructure.

Image via Shutterstock

 

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