Picture this: the AI landscape shattering into rival factions by 2026, where some players rake in the profits while others pour in endless cash. It's a thrilling yet turbulent scenario that begs the question – will you bet on the builders or the spenders? But here's where it gets controversial: could this division expose a massive AI bubble that's been building for years?
The AI industry is poised for a significant split in 2026, as recent market turbulence hints at deeper shifts ahead.
The final quarter of 2025 was a wild ride of tech stock plunges and rebounds, driven by convoluted deals, heavy borrowing, and inflated prices that sparked worries about an impending AI bubble bursting.
This instability might just be a preview of how AI funding will transform, with investors sharpening their focus on distinguishing between those burning through money and those actually generating it, as explained by Stephen Yiu, the chief investment officer at Blue Whale Growth Fund.
Especially for everyday investors dabbling in AI via exchange-traded funds (ETFs), which are like baskets of stocks you can buy and sell easily on the market, there's often little differentiation made between businesses that have innovative products but lack a solid revenue strategy, those hemorrhaging funds to build AI tech, or the recipients of AI-related expenditures, Yiu shared with CNBC.
Up until now, 'it feels like every player in the game is a winner,' but AI is still in its infancy, he noted. 'It's crucial to draw clear lines between these different types of companies,' and 'that's likely what the market will begin emphasizing,' Yiu added.
To visualize this, imagine a tablet screen reflecting binary code – a nod to the digital underpinnings of apps from giants like Google, Amazon, Facebook, and Apple, captured in a photo from April 20, 2018, in Paris by Lionel Bonaventure for AFP and Getty Images.
Yiu identifies three main groups: private ventures or startups, publicly traded AI spenders, and firms providing AI infrastructure.
The first category, featuring names like OpenAI and Anthropic, attracted a staggering $176.5 billion in venture capital during the first nine months of 2025, according to PitchBook data. On the flip side, tech titans such as Amazon, Microsoft, and Meta are the heavy hitters writing the checks to infrastructure providers like Nvidia and Broadcom.
At Blue Whale Growth Fund, they evaluate a firm's free cash flow yield – essentially, the cash left over after covering operational costs and investments – compared to its share price, to gauge if the valuation makes sense. (For beginners, think of it as checking if a company is producing enough spare cash to justify its expensive stock price.)
Many in the elite Magnificent 7 group are 'trading at a notable premium' ever since they ramped up AI investments, Yiu pointed out.
'When assessing AI valuations, I'm hesitant to invest – even though I'm optimistic about AI's global impact – in the spenders,' he said, preferring instead to 'be on the benefiting side' as AI outlays increasingly strain corporate finances.
The 'excessive optimism' in AI is 'focused on specific areas rather than the whole market,' Julien Lafargue, Barclays Private Bank and Wealth Management's chief market strategist, told CNBC.
The real danger lurks with firms capitalizing on the AI boom through investments but without real profits – 'take quantum computing companies as an example,' Lafargue mentioned.
'In these situations, decisions seem fueled more by hope than concrete achievements,' he continued, stressing that 'distinguishing between them is essential.'
And this is the part most people miss: This push for differentiation also mirrors a shift in how big tech operates. Once lean and agile, these companies are now accumulating hefty assets like technology, energy sources, and land to fuel their aggressive AI ambitions.
Firms such as Meta and Google have evolved into massive operators that pour resources into graphics processing units (GPUs for short, which are powerful chips crucial for AI computations), data centers, and AI-centric products, altering their risk levels and operational models.
Dorian Carrell, head of multi-asset income at Schroders, argued that treating these giants like traditional software companies with minimal capital expenses no longer fits – particularly as they're still scrambling to finance their AI visions.
'We're not claiming it won't succeed or deliver in the coming years, but we're questioning if such steep multiples, packed with high growth assumptions, are justified,' Carrell explained on CNBC's 'Squawk Box Europe' on December 1.
Tech firms turned to bond markets for AI funding this year, but lenders eyed their debt reliance warily. While Meta and Amazon secured such financing, 'they remain net positive in cash,' noted Ben Barringer, Quilter Cheviot's global head of technology research and investment strategist, on CNBC's 'Europe Early Edition' on November 20 – a key contrast to entities with shakier financials.
The private debt arena 'promises to be fascinating in the year ahead,' Carrell added.
If AI revenue growth doesn't keep pace with escalating costs, profit margins will shrink, prompting investors to reevaluate their gains, Yiu warned.
Moreover, disparities in performance could intensify as hardware and systems lose value over time. AI spenders must account for this in their planning, Yiu emphasized. 'It hasn't hit the profit and loss statements yet. Starting next year, it will progressively affect the figures.'
'In short, we'll witness increasing separation.'
But here's the controversial twist: Is it really smart to avoid AI spenders, as Yiu suggests, or could their heavy investments position them for dominance once the technology matures? And what about the ethical dilemmas of rushing into unproven areas like quantum computing – are we chasing hype over substance? I'd love to hear your takes: Do you think this splintering is a sign of a healthy evolution or just the calm before the bubble bursts? Share your thoughts in the comments – agreement, disagreement, or a fresh perspective welcome!
