The AI investment boom that captivated markets in early 2026 is now fracturing, revealing sharp divisions between companies riding genuine demand and those propped up by complex financing arrangements. Nigel Green, CEO of deVere Group, one of the world’s largest independent financial advisory organizations, sounded the alarm this week, urging investors to rethink their approach as the AI trade’s once unshakable momentum splinters. What had been a near-unified bullish narrative is now splintering under the weight of market realities, exposing vulnerabilities that could reshape portfolios through the remainder of the year.
Global spending on AI is set to surpass $2.5 trillion in 2026, but the disconnect between infrastructure investment and actual enterprise AI revenue growth has become impossible to ignore. While companies are pouring roughly $400 billion into AI infrastructure; data centers, chips, and cloud computing capacity; enterprise AI revenue is lagging far behind at around $100 billion. This growing chasm has rattled investor confidence, with a Bank of America survey finding that 45% of fund managers now see an AI bubble as the biggest tail risk to markets, a dramatic rise from just 11% a few months ago.
Over half believe AI stocks are already trading in bubble territory. The week’s market action underscored these tensions vividly. Asian tech stocks slipped, led by a 1% drop in the MSCI Asia Pacific Index and a 1% decline in South Korea’s Kospi, reflecting jitters about the tech rally’s sustainability.
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On Wall Street, the S&P 500 pulled back from record highs, semiconductor stocks declined more than 1% even as Nvidia’s shares advanced. Yet even Nvidia, a darling of the AI boom, saw sharp volatility. After reports emerged that Nvidia was seeking a payment guarantee of up to $250 billion for OpenAI’s data center lease and exploring an additional $350 billion in financing, its market cap fell below Apple’s for the first time in more than a year, and its credit default swap premium surged by a record amount.
The story was similar for SK Hynix, a major chipmaker that posted record quarterly revenue with a 257% year-over-year increase and a 76% operating margin, yet still saw its shares fall 9% on the earnings call. This paradox, strong financial performance met with sharp stock declines, reflects the growing skepticism around the AI trade’s sustainability. Even SpaceX, fresh off strong earnings, tumbled 14% ahead of a $101 billion share unlock, highlighting how financing events and market sentiment now overshadow fundamentals.
Nigel Green’s message to investors is clear: the days of treating the AI trade as a monolith are over. “The AI trade stopped being a single story months ago,” he said. “Some companies are seeing real, measurable demand for physical components that power this build-out.
Others rely increasingly on vendor financing arrangements to sustain their growth narrative. Lumping them together is no longer defensible.” His advice is to differentiate within the sector, identifying which companies stand on solid demand and which are propped up by complex financial engineering. Investors must also pivot their focus from headline growth stories to the underlying balance sheets.
The stocks under most pressure are not simply those with the largest AI infrastructure spend but those carrying heavy financing burdens and debt guarantees. SpaceX’s market value has erased roughly $1.2 trillion since its June IPO, pressured by lock-up expirations and setbacks in its Starship tests. Meanwhile, tech giants Alphabet, Amazon, Meta, and Microsoft are ramping capital expenditures by 77% to a record $725 billion in 2026, far exceeding analyst expectations, backed by a trillion-dollar backlog of contractual commitments.
Yet this capital intensity is not translating into smooth stock performance, as markets scrutinize how these expenditures are financed. Volatility around earnings dates is another hallmark of the current environment. The sector’s price-to-earnings ratio has climbed above 40, a level last seen before the dot-com crash.
Sharp single-day moves; like SpaceX’s 14% drop despite strong earnings; demonstrate how financing conditions can overwhelm fundamentals in the short term. Investors need to size their positions carefully, recognizing that sudden swings on financing news can move stocks 5% to 10% or more in either direction, disrupting any hopes for a steady, predictable trend. This fractured market landscape demands a more sophisticated, nuanced approach to AI investing.
The companies delivering genuine demand-driven growth; like Micron, Applied Materials, and Cisco; have posted strong earnings buoyed by real shortages of components and cloud-provider orders. Cisco, for example, raised its 2026 revenue guidance to nearly $63 billion, citing solid AI data center demand. These firms contrast sharply with others whose growth depends heavily on vendor financing, debt guarantees, or optimistic valuations disconnected from immediate revenue.
The warning signs are unmistakable: strong earnings alone no longer guarantee share price support. Investors who wait for more clarity risk missing the crucial window to reposition. The market is rapidly parsing which parts of the AI trade represent sustainable value and which are vulnerable to a retrenchment.
The companies with robust balance sheets, genuine demand, and transparent financing structures are best positioned to weather the turbulence. The AI trade’s trajectory is unlikely to smooth out soon. The sector is entering a phase of episodic volatility driven by earnings reports and financing developments rather than steady growth.
Investors must embrace this new normal, adapting their strategies to manage risk and capitalize on real opportunities. The market’s earlier euphoria has given way to a more discerning reality check, but the long-term potential of AI remains significant for those who navigate these choppy waters wisely. Nigel Green sums it up best: “The investors who do well in the rest of 2026 won’t be those asking if AI as a sector is a good bet anymore.
The question is which parts of the AI trade are built on real demand and which rely on financing structures yet to prove themselves. Getting that distinction right, and acting decisively, will define success in the months ahead.” For AI investors, the time to act is now, before the next wave of volatility reshuffles the deck once again. This moment marks a turning point.
The AI trade is no longer a single, unified story but a fractured landscape. The winners will be those who recognize the fault lines and adjust their sails accordingly – because the storm is just beginning.
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