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Home»Finance News»Small companies rising quickly to rival Big Tech as AI ‘s best trade
Finance News

Small companies rising quickly to rival Big Tech as AI ‘s best trade

January 17, 2026No Comments4 Mins Read
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Small companies rising quickly to rival Big Tech as AI ‘s best trade
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Artificial intelligence is no longer a narrow technology trade. It is reshaping energy markets, infrastructure spending, and portfolio construction. Investors who focus only on chips and software risk missing where the next phase of value is occurring, according to investing experts on this week’s episode of CNBC’s “ETF Edge.”

Some of the trends and innovations driving the market, and the rapid scaling of companies, are tied to AI’s physical requirements. Power, cooling, grid stability, and data center efficiency have become binding constraints. Just look at the stock price of Bloom Energy, which for years after its 2018 IPO struggled to eke out a return above its IPO price. Since last year, when its onsite fuel cells began being ordered furiously for data centers, Bloom has seen its shares shoot up over 500% and the company reached a market cap above $30 billion.

Many opportunities are being created in small- and mid-cap companies for investors. Firms that once sat outside the market’s focus are now “very quickly moving up the cap table,” TCW Group global head of distribution Jennifer Grancio said on “ETF Edge” on Monday. In many cases, these companies operate in narrow segments with limited competition, allowing fundamentals to improve faster than investor awareness.

Energy reliability is the central issue. In recent years, as the cost of renewable energy sources came down and became competitive with fossil fuel sources, the market debated “How much regularity could we get out of wind, or could we get out of solar?” Grancio said. But AI has shifted the conversation since data centers cannot tolerate intermittency, requiring a constant supply of power to avoid unintended downtime.

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That reality has driven “a huge shift towards nuclear,” according to Grancio, including renewed investment in servicing existing plants and developing small modular reactors. These projects are spawning new suppliers and accelerating growth for specialized players that sit upstream of utilities and hyperscalers.

Nuclear power ETFs

  1. First Trust Bloomberg Nuclear Power ETF (RCTR)
  2. VanEck Uranium and Nuclear ETF (NLR)
  3. Themes Uranium & Nuclear ETF (URAN)
  4. Range Nuclear Renaissance Index ETF (NUKZ)
  5. Global X Uranium ETF (URA)

Efficiency inside the data center is equally critical. As AI workloads expand, cooling and power management have become the chokepoints. Investors are increasingly drawn to companies that are “one or two in their field” and “the best at a certain technology” particularly where alternatives are limited, Grancio said.

The structure of these markets matters. In some cases, there are “only a few providers” bordering on oligopolies, Grancio said. That concentration creates operating leverage, but it also means missteps can be costly.

Actively managed ETFs are gaining traction as a result. While passive indices can capture broad market returns and the indexes do add new companies as components as they scale, active strategies aim to identify them earlier and hold them through multiple phases of growth.

But the risks can be significant. Some parts of the AI-powered ecosystems include “small, financially weak companies” that are leveraged to electricity demand, VanEck CEO Jan van Eck. “That also means you get a lot of volatility along the way,” he said on “ETF Edge.”

As a result, he said no single AI theme should dominate an investor’s asset allocation. “You don’t want to overweight them in your portfolio,” Van Eck said.

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He described Van Eck’s nuclear ETF as having traded at “nosebleed levels” last year before it came down to a more reasonable entry point for new investors.

The ETF experts said that as investors bring the AI theme into their portfolio construction in a more targeted way in 2026, active rebalancing and clear risk expectations will allow investors to stay invested without chasing peaks or panicking at drawdowns.

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