How the AI market could splinter in 2026

The AI ​​market is expected to fragment in 2026.

The last three months of 2025 have been a rollercoaster of tech sell-offs and booms, with round-robin deals, debt issuances and high valuations fueling concerns about an AI bubble.

This volatility could be an early sign of how AI investing will evolve as investors pay more attention to who is spending money and who is making money., According to Stephen Yiu, chief investment officer of Blue Whale Growth Fund.

Investors, especially retail investors with exposure to AI through ETFs, often don’t distinguish between companies that have a product but no business model, companies burning cash to fund AI infrastructure, or those on the receiving end of AI spending, Yiu told CNBC.

So far “every company seems to be winning” but He said artificial intelligence is still in its infancy. Yiu added that “it’s very important to distinguish” between different types of companies, which “is what the market can start to do.”

He sees three camps: private companies or startups, listed AI spenders, and AI infrastructure firms.

The first group, which includes OpenAI and Anthropic, provided $176.5 billion in venture capital in the first three quarters of 2025, according to PitchBook data. By the way, like Big Tech names Amazon, Microsoft And Meta These are the ones who cut off the controls of artificial intelligence infrastructure providers such as Nvidia And broadcom.

The Blue Whale Growth Fund measures its free cash flow yield, which is the amount of money a company produces after capital spending, relative to its stock price to see if valuations are justified.

Yiu said most companies in the Magnificent 7 have “traded at a significant premium” since they began investing heavily in AI.

“When looking at valuations in AI, even though I believe in how AI will change the world, I wouldn’t want to be among the AI ​​spenders,” he added, adding that his firm would prefer to be “on the receiving end” as AI spending stands to further impact company finances.

The AI ​​“foam” is “concentrated in specific segments rather than the broader market,” Julien Lafargue, chief market strategist at Barclays Private Bank and Wealth Management, told CNBC.

Lafargue said the greater risk lies in companies that have secured investment from the AI ​​bull run but have yet to generate profits (for example, some quantum computing-related companies).

“In these cases, investor positioning appears to be driven by optimism rather than concrete results,” he added, saying “diversification is key.”

The need for differentiation also reflects the evolution of Big Tech business models. Once asset-heavy firms are becoming increasingly asset-heavy as they gobble up the technology, power, and terrain needed for bullish AI strategies.

Companies like Meta and Google have turned into hyperscalers investing heavily in GPUs, data centers, and AI-focused products, changing their risk profiles and business models.

Dorian Carrell, head of multi-asset revenue at Schroders, said it may no longer make sense to value these companies as software and capex-light plays; especially as companies are still trying to figure out how to fund their AI plans.

“We’re not saying it won’t work, we’re not saying it won’t happen in the next few years, but we’re saying: Would you pay such a high multiple when you have such high growth expectations?” Carrell told CNBC’s “Squawk Box Europe” on Dec. 1.

Tech has turned to debt markets this year to fund AI infrastructure, but investors have been wary of relying on debt. Even though Meta and Amazon raise funds this way, “they’re still in a net cash position,” Ben Barringer, global head of technology research and investment strategist at Quilter Cheviot, told CNBC’s “Europe Early Edition” on Nov. 20; This is a significant difference from companies whose balance sheets may be tighter.

Private debt markets “will be very interesting next year,” Carrell added.

If rising AI revenues fail to exceed these expenses, margins will be squeezed and investors will question their return on investment, Yiu said.

Additionally, as hardware and infrastructure lose value, performance differences between companies may increase further.. Yiu added that those who spend on artificial intelligence should take their investments into account. “It’s not part of the profit and loss yet. It will gradually mix up the numbers from next year.”

“So there will be more and more differentiation.”