The age-old Wall Street adage advising investors to “sell in May and go away” has been completely debunked this spring, proving irrelevant in the current macroeconomic environment. While a significant portion of market participants focused their attention on climbing energy prices and concerns over the potential overvaluation of mega-cap tech stocks, the financial markets chose to reward what appears to be the most significant structural shift since the onset of the artificial intelligence cycle. The broadening of the AI trade, fueled by continuously rising capital expenditure (CapEx) forecasts from technology giants, is fundamentally altering the rules of the game and driving massive demand across the entire supply chain and infrastructure ecosystem, from chip manufacturers to energy and cooling infrastructure firms.

Expanding the AI Trade Beyond Big Tech

The recent quarterly earnings season provided definitive confirmation of a profound trend reversal within the tech infrastructure and data center sector. Leading companies showcased an unprecedented surge in capital expenditures dedicated to developing and training artificial intelligence models, breathing new life into the demand for specialized chips, advanced memory components, and communication equipment. Consequently, the forward price-to-earnings multiples of numerous industrial tech firms have been pushed to highly attractive levels, signaling clear entry opportunities for both value and growth investors. A prominent example is Micron Technology, which is currently capitalizing on peak demand for High Bandwidth Memory (HBM)—a critical component in the most advanced AI servers. Despite a staggering rally of over 900% in the past year, Micron continues to trade at a remarkably low forward P/E ratio of just nine. This valuation is supported by phenomenal expectations of nearly 700% growth in earnings per share over the coming year, illustrating how the market sometimes struggles to fully price in the speed at which these infrastructure companies convert order backlogs into dramatic bottom-line profitability.

The Numbers Behind the Growth and Investor Psychology

This aggressive growth trend is not confined to a single company; rather, it reflects a broad and deep sectoral phenomenon permeating multiple layers of the market. According to investment bank Barclays, the EPS growth of the technology sector, even when stripping out the performance of the “Magnificent Seven,” hit a record high of over 51% annualized during the first quarter of 2026. Forecasts for the upcoming quarters point to a continuation and even an acceleration of this financial momentum. These figures expose a fascinating psychological mechanism among the retail investing community and hedge funds. While many retail investors hesitate to enter the market due to an “anchoring bias” to past prices and a fear of missing out (FOMO) often accompanied by the dread of a sudden correction, the financial and fundamental data suggest that the real potential of second- and third-tier companies in this space has not yet been fully realized. Smart money, managed by institutional entities, already understands that the next wave of artificial intelligence winners is taking shape right now, far from the main headlines.

Technology Picking Technology: The Era of Quantitative Models

In the modern era, where the volume of financial data vastly exceeds traditional human processing capabilities, the comparative advantage is rapidly shifting into the hands of algorithms and advanced trading systems. Financial models based on machine learning now provide a rational, cold analytical perspective, free from emotional background noise or cognitive biases. These systems enable the precise identification of companies with outsized growth potential and favorable risk-reward profiles from among thousands of traded equities. Strategies relying on artificial intelligence for stock selection have managed to generate returns exceeding 200% since late 2023, producing significant outperformance of more than 120% relative to the broader S&P 500 index. In May alone, these algorithms identified in real-time numerous tech infrastructure stocks that subsequently posted price increases of 20% or more, unequivocally proving the crucial importance of a systematic, data-driven approach in a volatile market environment.

As we advance into the second half of the decade, it becomes abundantly clear that the artificial intelligence investment cycle is far from over, and it is highly likely we are still merely experiencing its early innings. The next phase in the market’s evolution will not be characterized by a blind, horizontal dispersion of capital to any company incorporating advanced technologies, but rather by a rigorous selection of businesses demonstrating proven bottom-line growth, steady increases in free cash flow, and reasonable multiples relative to their growth projections. For market participants and institutional investors, the true challenge now is to accurately identify the infrastructure providers, enterprise software solutions, and industrial firms that constitute the operational backbone of this revolution. Those who manage to align their portfolio asset allocation with the clear roadmap drawn by the unprecedented capital budgets of corporate giants may well find themselves in a commanding leadership position heading into the quarters ahead.