The AI bull market narrative has reached a "judgment moment"! The financial reporting season for technology giants will test the realization progress of AI capital expenditures on a massive scale.

With the bull market sentiment surrounding global stock markets and the dominance in the U.S. stock benchmark S&P 500 Index of the mega-cap U.S. tech giants, whose market value weights exceed 20%, the earnings reports of these companies are entering an intensive phase this week. Alphabet Inc. Class C parent company Alphabet (GOOGL.US), as well as Microsoft Corporation (MSFT.US), Amazon.com, Inc. (AMZN.US), Meta parent company Facebook (META.US), and Apple Inc. (AAPL.US) will all be releasing their latest quarterly earnings. Investors' focus has shifted from whether the individual giants' performance meets expectations to a more broad and interconnected key question regarding the fate of global stock markets: can these trillion-dollar giants maintain their aggressive AI computing power infrastructure investment cycle driven by the increasingly clear AI revenue/AI monetization path? Heath Terry, the head of technology and communications research at Wall Street financial giant Citigroup, pointed out in a recent research report that despite high capital expenditure expectations, there may only be a moderate increase in the near term. Following a significant increase in AI capital expenditures over the past year - well above market expectations, the continuing scale of investment reflects an accelerating demand for AI computing power infrastructure and an unprecedented global dynamic of investing heavily in AI data centers. However, clear constraints are starting to emerge. Terry added that while global technology companies generally have a strong desire to deploy more capital towards cutting-edge AI tools like AI AGENT (Agentic AI), they are facing real constraints, including a shortage of cloud AI computing power infrastructure resources, electricity capacity, skilled labor, and ongoing shortages and regulatory bottlenecks in approval processes. Even as competition intensifies, these factors could limit the speed of expansion in enterprise AI deployment. Therefore, Terry believes that investors' focus is gradually evolving; the future debate may no longer simply focus on how much money companies are willing to spend on AI, but on how effectively these expenditures can be translated into actual revenue or profit growth. While the market generally expects improvements in AI-driven revenue and enterprise productivity in the future, there is an increasing demand for early evidence to continue demonstrating that revenue growth can outpace the ongoing rise in capital intensity surrounding AI. Terry stated that as AI investments drive the entire technology industry, this earnings season for tech giants and even for the entire tech sector will be a critical test - namely, providing enough evidence to show that these expenditures can ultimately drive a sustainable and highly profitable growth trajectory. The stock market has already shrugged off the war! The new bull market narrative driven by the "AI bull market" is unfolding As model sizes, inference chains, and multimodal/agent-based Agentic AI workloads drive exponential expansion of computing resources, the main focus of tech giants' capital expenditures is increasingly shifting towards concentrated AI computing power infrastructure. Global investors are anchoring the "semiconductor stock bull market narrative" around the new product iterations and AI computing cluster delivery expectations of NVIDIA Corporation, Alphabet Inc. Class C TPU clusters, and AMD, making it one of the most certain investment narratives in the global stock market; while also indicating that investments related to electricity, liquid cooling systems, optical interconnect supply chains, and other sectors closely related to AI training/inference will follow the leaders in AI computing power such as NVIDIA Corporation, AMD, Broadcom Inc., Taiwan Semiconductor Manufacturing Co., Ltd. Sponsored ADR, and Micron Technology Inc., even as the geopolitical situation in the Middle East faces uncertainty. Recent forecasts released by strategists at Bank of America Corp show that, driven by the accelerating growth of leaders in the global AI computing industry chain (NVIDIA Corporation, Broadcom Inc., Taiwan Semiconductor Manufacturing Co., Ltd. Sponsored ADR, and Marvell Technology, Inc.) and in areas such as storage/logic chips, advanced 2.5D/3D packaging, data center power chains, the total size of the global semiconductor market is expected to reach $2 trillion by 2030, with an annual compound growth rate of 20% from 2025 to 2030. In comparison, the global semiconductor market was expected to be less than $1 trillion by at least 2025. As the benchmark of the South Korean stock market - KOSPI, dominated by Samsung and SK Hynix with high weightings, hits historic highs under the heavy pressure of geopolitical tensions in the Middle East and the Taiwan Semiconductor Manufacturing Co., Ltd. Sponsored ADR, a major winner in the AI boom with the title of "Chip Manufacturing King," drives the Taiwanese stock market to new highs, coupled with the Philadelphia Semiconductor Index, known as the "chip stock barometer," posting a record 18 consecutive trading days of gains, investors are increasingly confident that the "AI computing power investment theme" can overpower all the noise in the stock market, especially those related to geopolitical issues. At the same time, the distribution of weights in the value chain surrounding AI computing power infrastructure is beginning to shift. Extraordinary alpha returns in the market will no longer be limited to the strongest players in the AI GPU/AI ASIC fields but will systematically spread to the full stack of AI computing power infrastructure layers, including CPUs, storage, PCBs, liquid cooling systems, ABF substrates, and extensive wafer manufacturing. "The reason why the market rebound is so strong is that investors are full of enthusiasm and confidence in the strong profit trajectory of tech companies driven by the wave of AI computing power expenditure, and these tech stocks account for nearly half of the total market value of the S&P 500." said Mark Zandi, Chief Economist at Moody's Corporation, "In the face of this war, the market has shown great resilience, and it is rising strongly on expectations that the geopolitical issues regarding the Middle East are likely to be very manageable." Stock strategists at BlackRock, Inc., the largest asset management giant on Wall Street, have shifted back to "overweight" U.S. and emerging market stock assets, mainly because they believe that the substantial damage to global economic growth caused by the recent geopolitical conflicts in the Middle East "is likely to be very manageable." In terms of core investment themes/investment trends, strategists at BlackRock, Inc. are particularly bullish on semiconductor stocks closely related to AI computing power infrastructure, such as the leading players in the AI computing industry chains on the U.S., South Korean, and Taiwanese stock markets. BlackRock, Inc. strategists wrote, "Even during the geopolitical conflicts in the Middle East, corporate profit expectations continue to rise, and much of the logic and reasons are related to the strong demand for AI computing power brought by the AI-related investment theme." The narrative of the AI bull market faces a crucial "rational test" The market's overall outlook on the earnings season for tech giants is optimistic, but it is not "unconditional or blindly positive." As forecasted by Citigroup strategists, the current market trend is that AI capital expenditure is still supporting global stock market risk appetite, and the earnings reports of tech giants are seen as a key juncture to test whether this AI bull market can continue. The core driver of the recent rebound in U.S. stocks has been the strong expectations for cloud AI capital expenditure, with the S&P 500 and Nasdaq significantly rebounding since the end of March, and the Philadelphia Semiconductor Index showing even greater gains; meanwhile, Microsoft Corporation, Alphabet, Meta, Amazon.com, Inc., and Apple Inc., among others, will soon unveil their earnings reports, with the market anchoring the scale of their 2026 AI computing infrastructure investments in the range of $600-700 billion. Therefore, what the market is truly concerned about is not whether EPS exceeds expectations for a single quarter, but whether AI spending can continue to drive strong revenue for cloud computing businesses, AI-driven advertising revenue, enterprise AI computing demand, and overall profit margin resilience. The framework provided by Citigroup is crucial - the AI investment cycle remains strong, but constraints are emerging. Heath Terry emphasizes that while capital expenditure expectations are still high, any short-term increases are likely to be moderate, as factors such as electricity capacity, skilled labor, and regulatory approval are becoming bottlenecks to expansion. In other words, the market is no longer simply rewarding "who spends the most money," but is beginning to ask: can these AI capital expenditures revenue/profit growth, customer commitments, strong demand for cloud AI computing power, and sustainable profits. In other words, the AI bull market is transitioning from the first phase of "the bigger the capital expenditure, the better" to the second phase of "the return on investment must be validated." From an investment strategy perspective, the narrative of the AI computing power bull market is not over yet, but there will be noticeable differentiation within it. Morgan Stanley's logic is consistent with Citigroup's: the first signal of determining the return on AI investments is revenue acceleration, rather than simply the scale of AI CapEx (AI capital expenditure). Alphabet Inc. Class C needs to demonstrate that revenue from cloud computing and cloud-based AI computing can absorb depreciation pressure; Microsoft Corporation needs to prove that the demand for Azure computing power still exceeds supply; Meta needs to show that the cash flow growth driven by AI advertising is sufficient to cover the expansion of AI infrastructure; and Amazon.com, Inc. needs to demonstrate that the commitments of large AWS customers and the path to realizing the capacity of AI computing infrastructure in 2027-2028 are credible. At the same time, another major Wall Street financial giant has raised its year-end target for the S&P 500 to 7600 points, with one of the reasons being the upward revision of profits and the momentum of the technology sector driven by AI, indicating that mainstream funds on Wall Street still tend to believe that the AI market is not done yet. However, this does not mean that the risk of an "AI bubble bursting" does not exist. The expansion of AI data centers is already beginning to squeeze free cash flow, forcing tech giants to cut other costs; recent layoffs or buyouts of employees by companies like Meta and Microsoft Corporation are to allocate budgets for AI data center construction and highly paid AI talent. This signal indicates that AI investment has entered a stage of extremely high capital intensity, and management must demonstrate ROI. If the earnings reports show that the acceleration of revenue from cloud computing, AI-related businesses, and demand for cloud computing power is insufficient to cover capital expenditures, the market will first penalize the most overvalued, weakest cash flow, and most opaque path to returns in AI assets. Therefore, investors generally strongly believe that the AI computing power bull market is far from over, but this earnings season is a "ROI verification moment," not a "celebration." The overall trend of the AI investment theme remains bullish, but the real change is that funds will continue to concentrate on the hardest, most tightly supplied, and most commercially clear aspects of cloud AI computing power orders, rather than on the broader AI concepts. Whether the global stock market bull run continues to soar depends on whether the five major tech giants can provide clear expansion trajectories for three key things simultaneously: continued strong AI capital expenditure, increasingly clear paths to realize AI-related revenue, and no out-of-control profit margin/cash flow pressures.