Micron Technology’s recent earnings report not only breathed new life into the artificial intelligence (AI) market but also shed light on the escalating costs associated with it. The memory chipmaker is the first to reap the benefits of burgeoning AI demand, which is currently challenged by a supply bottleneck. The critical question remains: who will bear the financial burden next? Will it fall on Big Tech, device consumers, cloud service users, AI implementers, or even the broader economy?
This conundrum has led to Micron’s stock experiencing a surge while still appearing reasonably priced based on Wall Street’s profit projections. The company’s trailing price-to-earnings (P/E) ratio reflects profits from the past year, whereas the forward P/E ratio is based on analysts’ estimates for the upcoming year. Micron’s stock trades around 9 times expected profits for the next 12 months, a valuation lower than that of major players like Nvidia, the S&P 500, and tech giants such as Apple, Amazon, Alphabet, Microsoft, and Meta.
The underlying reason for this disparity is straightforward; analysts forecast a significant profit spike for Micron. The company has guided investors towards an impressive projection of nearly $50 billion in quarterly revenue and approximately $31 in adjusted earnings per share for its fiscal fourth quarter, well above Wall Street’s predictions. Additionally, Micron reported a gross margin of 84.9%, with expectations of an increase to roughly 86% in the next quarter due to tightening memory supply.
However, it’s important to note that Micron’s profit surge does not exist in isolation. The ripple effects of rising component costs are already evident in the market. For instance, Apple saw its stock drop by 6% after announcing price increases on selected Macs and iPads. This illustrates the growing pressure on suppliers and the discomfort it generates among buyers.
For other tech behemoths like Microsoft, Amazon, and Alphabet, the financial implications manifest through heavy investments in AI infrastructure. These companies are attempting to offset these expenses via cloud services, enterprise software, subscriptions, and AI tools. The success of this strategy hinges on whether customers are willing to cover these increased costs. If they accept higher prices, these investments may translate into growth; however, if they resist, it could negatively impact profit margins and lead to depreciation.
The broader market is already questioning this dynamic. After Micron’s earnings report, stocks in the “Magnificent Seven”—a group that includes key players in the AI sector—declined, returning to levels not seen for approximately nine months. This stagnation raises concerns about the sustainability of the AI sector’s valuation.
In a theoretical ideal, the ultimate cost-bearer should be productivity itself. If AI enables companies to automate operations, boost sales, and maintain profit margins, the financial burden that comes with new hardware could potentially be absorbed. However, if the expected benefits from AI lag or prove to be exaggerated, it could lead to a downturn in orders, a balance in supply and demand, and an erosion of pricing power. The outcome of this scenario will be closely watched as the AI landscape continues to evolve.
