How the AI ​​market could divide in 2026

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

The final three months of 2025 have been a rollercoaster of tech sales and rallies, as circular trading, debt issuances and high valuations fueled concerns about an AI bubble.

Such volatility could be an early sign of how AI investments are set to evolve, as investors become more attentive to who is spending and who is making money., according to Stephen Yiu, chief investment officer at Blue Whale Growth Fund.

Investors, particularly retail investors who gain exposure to AI through ETFs, have generally not distinguished between companies with a product but no business model, those spending money to fund AI infrastructure, or those receiving AI spending, Yiu told CNBC.

So far, “every company seems to be winning,” but AI is in its infancy, he said. “It’s very important to differentiate” between different types of businesses, and that’s “what the market could start to do,” Yiu added.

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

The first group, which includes OpenAI and Anthropic, attracted $176.5 billion in venture capital in the first three quarters of 2025, according to PitchBook data. Meanwhile, big tech names such as Amazon, Microsoft And Meta are those who cut off controls from AI infrastructure providers such as Nvidia And Broadcom.

The Blue Whale Growth Fund measures a company’s free cash flow performance, which is the amount of money a company generates after capital expenditures, against its stock price, to determine whether valuations are justified.

Most Magnificent 7 companies are “trading a significant premium” since they began investing heavily in AI, Yiu said.

“When I look at AI valuations, I wouldn’t want to position myself — even though I believe in how AI will change the world — among the AI ​​spenders,” he said, adding that his company would prefer to be “on the receiving end” because AI spending is expected to have an additional impact on the company’s finances.

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

The biggest risk lies in companies that are getting investment from the rise of AI but have yet to generate profits – “for example, some companies related to quantum computing,” Lafargue said.

“In these cases, investor positioning seems more motivated by optimism than by tangible results,” he added, believing that “differentiation is essential.”

The need for differentiation also reflects an evolution in Big Tech’s business models. Companies that were once asset-light are getting more and more as they gobble up the technology, energy and land needed for their bullish AI strategies.

Companies like Meta and Google have transformed into hyperscalers that invest heavily in GPUs, data centers and AI-based products, changing their risk profile and business model.

Dorian Carrell, head of multi-asset income at Schroders, said valuing these companies like software and light investments may no longer make sense, especially as companies are still figuring out how to finance their AI projects.

“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 pay such a high multiple with such high growth expectations,” Carrell told CNBC’s “Squawk Box Europe” on Dec. 1.

Tech has turned to debt markets to finance AI infrastructure this year, although investors have been cautious about relying on debt. Even though Meta and Amazon raised money this way, “they’re still positioned in net cash,” Ben Barringer, global head of technology research and investment strategy at Quilter Cheviot, told CNBC’s “Europe Early Edition” on Nov. 20 — an important distinction from companies whose balance sheets may be tighter.

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

If incremental AI revenue does not exceed these expenses, margins will contract and investors will question their return on investment, Yiu said.

Additionally, performance gaps between companies could widen further as equipment and infrastructure depreciate.. AI investors will need to take this into account in their investments, Yiu added. “It’s not yet part of the P&L. Starting next year, gradually, it will blur the numbers.”

“So there’s going to be more and more differentiation.”