By Lina Irawan 
The global financial markets are navigating a period of profound uncertainty and exhilarating opportunity, largely driven by the explosive growth and transformative potential of artificial intelligence. Following a jittery start to the week, which saw significant sell-offs fueled by anxieties over AI’s disruptive economic impact, investor sentiment appears to be staging a cautious recovery. This morning’s uptick in S&P 500 futures, building on yesterday’s robust gains, suggests a market grappling with the dual narratives of technological revolution and potential overvaluation. All eyes are now firmly fixed on Nvidia’s highly anticipated Q4 2025 earnings call this evening, an event widely regarded as a pivotal barometer for the health and trajectory of the entire AI sector.
Monday’s market downturn, characterized by a 1% dip in the S&P 500, was attributed to a growing chorus of concerns that the rapid advancement of AI could unleash an "economic doom cycle." These fears encompass a spectrum of anxieties, from widespread job displacement across various industries to the potential for a speculative bubble reminiscent of the dot-com era, where valuations soared far beyond fundamental realities. The narrative of AI as a job destroyer, while still largely theoretical at scale, has resonated with some investors, prompting a retreat from riskier assets. However, the subsequent rebound, with yesterday’s 0.77% gain and today’s further positive momentum in futures trading, indicates a contingent of traders believes the initial panic was an overreaction. This resilience underscores the market’s inherent tendency to re-evaluate and often correct knee-jerk reactions, especially when a dominant technological theme is at play. The prevailing sentiment appears to be that the long-term opportunities presented by AI far outweigh the immediate, albeit significant, disruption risks, at least in the eyes of many institutional investors.
At the heart of this AI-driven market dynamic is Nvidia, a company whose graphics processing units (GPUs) and CUDA software platform have become the indispensable backbone of modern AI development. Nvidia’s technological dominance in producing the high-performance chips essential for training and running complex AI models has cemented its status as arguably the most critical component supplier in the burgeoning AI ecosystem. Its quarterly earnings calls are no longer just about a single company’s performance; they are seen as a proxy for the entire industry’s momentum, providing crucial insights into demand trends, capital expenditure cycles, and the overall pace of AI adoption.
Dan Ives, a prominent analyst at Wedbush, encapsulates the prevailing bullish sentiment surrounding Nvidia. "We will… be able to hear a pin drop on Street trading desks as the entire global market will be carefully watching these results and commentary," Ives told clients, highlighting the immense scrutiny and anticipation. He articulated a strong conviction that Nvidia is poised to "comfortably exceed estimates and guide above Street given continued positive data points through 4Q as well as seemingly healthy spending set up through 2026." This optimistic outlook is predicated on the unwavering demand from hyperscale cloud providers, enterprise clients, and research institutions all scrambling to build out their AI infrastructure. Ives and other bulls believe that the "AI gold rush" is still in its early stages, and Nvidia, as the primary picks-and-shovels provider, stands to benefit immensely from sustained, aggressive investment in AI capabilities. Their confidence stems from consistent reports of robust order backlogs, strategic partnerships, and a seemingly insatiable appetite for advanced AI compute power.
However, not all market watchers share this unbridled enthusiasm. Francesco Pesole at ING offered a more tempered and anxious perspective, cautioning clients that "It looks tentative ahead of today’s high-stakes Nvidia earnings. With some investor unease around AI stocks still lingering, Nvidia will probably need to beat consensus and offer strong guidance to provide meaningful reassurance." Pesole’s analysis underscores the precarious position of AI stocks, where elevated valuations have made them particularly sensitive to any deviation from lofty expectations. He starkly warned that "At this stage, the downside risks to global risk sentiment from a miss appear larger than the upside from a beat." This means that even a modest beat might not significantly propel the market higher, as much of the good news might already be priced in, while any sign of weakness or a conservative outlook could trigger a sharp sell-off, creating a ripple effect across the broader tech and AI-related markets. The "investor unease" Pesole references could stem from various factors, including concerns over the sustainability of current growth rates, the potential for increased competition in the long run, or broader macroeconomic headwinds that could eventually curb enterprise spending on AI.
Beyond Nvidia, the broader tech sector continues to exhibit a state of fragility. The Nasdaq Composite, heavily weighted towards technology stocks, remains down 1.63% year-to-date, a stark contrast to the S&P 500, which has managed a 0.65% gain over the same period. This divergence highlights a bifurcated market: while a few mega-cap tech players, largely those at the forefront of AI, have seen substantial gains, a broader swathe of the tech sector is struggling. Many companies are grappling with higher interest rates, slowing consumer demand, and the strategic pivot required to integrate AI into their operations, often at significant cost.
Adding to this concern, Bespoke Investment Group published an intriguing analysis of what they termed a "new ‘AI Doom’ basket." This collection, comprising 55 large-cap stocks that have recently been "punished by AI headlines," is now trading down to levels last seen in April of the previous year, coinciding with the "tariff tantrum" lows for the S&P 500. This "AI Doom" basket likely includes companies whose business models are perceived as vulnerable to AI disruption, those that have failed to adequately articulate an AI strategy, or simply those that have seen capital flow out towards the more direct beneficiaries of the AI boom. The comparison to a "tariff tantrum" – a period of market volatility driven by trade war fears – suggests that the current anxieties surrounding AI’s disruptive potential are as potent, if not more so, than previous geopolitical and economic shocks. It indicates a deep-seated apprehension among investors about the sweeping, unpredictable changes AI could bring to established industries and corporate profitability.
Perhaps the most vivid characterization of this underlying fragility and investor skittishness came from Xiao Lei, the head of research and chief economist at Hong Kong-based Kasikornbank. As quoted in the South China Morning Post, Lei described U.S. investors’ willingness to sell off in fear of AI with a poignant metaphor: "If you see a strong man suddenly break down in tears in a restaurant because there’s no chilli sauce on the table, you immediately understand that he must have been holding back those tears for a long time." This analogy speaks volumes about the latent anxieties within the market. The "chilli sauce" – a seemingly minor trigger – represents the "AI doom" headlines, while the "strong man holding back tears" symbolizes a market that has been under considerable pressure, perhaps overvalued, or burdened by other unresolved issues (like persistent inflation, geopolitical tensions, or the lingering effects of rapid interest rate hikes). It suggests that the AI fears are not isolated but rather the latest catalyst exposing deeper, pre-existing vulnerabilities.
Compounding these concerns, Goldman Sachs recently issued a significant warning regarding capital expenditures (capex) by the major AI hyperscalers – a term referring to the massive cloud computing providers like Amazon Web Services (AWS), Microsoft Azure, Google Cloud, and Meta. Their analysis estimates that hyperscaler capex is projected to reach an staggering $667 billion in 2026, marking a monumental 62% increase from the previous year. What makes this figure particularly alarming is that it crosses a critical threshold established during the notorious dot-com bubble of the late 1990s.
Ryan Hammond and his colleagues at Goldman Sachs noted, "Hyperscaler capex is now on pace to exceed 90% of cash flows this year, above the share during the Dot Com Boom." This comparison to the dot-com era is not made lightly. During that period, companies invested heavily in internet infrastructure, often without clear revenue models, leading to overcapacity and ultimately a spectacular bust. While the underlying technology and business models of today’s AI hyperscalers are far more robust and revenue-generating, the sheer scale of investment relative to cash flows raises questions about the sustainability of such rapid expansion. Overinvestment can lead to diminishing returns, increased debt, and pressure on profitability if demand doesn’t keep pace with the expanded capacity.
Furthermore, Goldman Sachs predicts that "A deceleration in the quarterly growth rate is likely in late 2026." This forecast suggests that the current explosive growth in AI infrastructure spending may not be indefinitely sustainable. Factors contributing to a potential slowdown could include market saturation, increased efficiency in AI hardware, or a macroeconomic downturn that causes enterprises to tighten their belts. The report explicitly warns that "The revenue growth and valuations of some AI infrastructure stocks appear vulnerable to a slowdown in capex growth." This vulnerability highlights the interconnectedness of the AI ecosystem; a slowdown in spending by the major cloud providers would inevitably impact companies like Nvidia and other hardware suppliers whose fortunes are tied directly to this capital expenditure.
Finally, the Goldman Sachs report touched upon the "dislocation between [Nvidia] price and earnings," and the inherent challenges of "delivering persistently strong returns amid fears of ‘over-earning.’" This point is crucial for understanding the current market psychology around Nvidia. Despite consistently blowing past earnings expectations, Nvidia’s stock price has often surged even further, creating a valuation premium. "Over-earning" implies that current profits are exceptionally high, potentially unsustainably so, and that these levels might attract intense competition or invite regulatory scrutiny. The "dislocation" suggests that the market’s enthusiasm, as reflected in the stock price, may have outpaced even Nvidia’s phenomenal financial performance, leaving less room for error and making the stock particularly susceptible to negative news or a shift in sentiment.
As the market awaits Nvidia’s critical earnings announcement, the underlying tension between boundless optimism and deep-seated caution remains palpable. Investors are not just looking for a strong quarterly report; they are searching for validation of the long-term AI thesis, a reassurance that the current wave of innovation is a sustainable revolution rather than a fleeting speculative frenzy. The outcome of this evening’s call will undoubtedly shape market trajectories, influence investment strategies, and either reinforce the AI boom or exacerbate existing anxieties, setting the tone for the remainder of 2026 and beyond.