As expectations for growth in the artificial intelligence (AI) industry collide with concerns over massive investment costs, global tech companies are ramping up fundraising and expanding investments. The key issue is whether astronomical investments will translate into actual profits. This week, the earnings reports from memory semiconductor firms and major U.S. tech companies are expected to serve as a litmus test for the sustainability of AI industry growth and investment.
According to Reuters on October 26, Anthropic, the developer of the generative AI model Claude, is pursuing the largest initial public offering (IPO) in history. The company is valued at up to $20 billion and aims to raise $10 billion. On the same day, Meta announced plans to raise up to $95 billion to expand its AI infrastructure investments.
The competition for funding in AI development has spilled over into the bond market, with Bloomberg reporting that AI-related funds raised in the global investment-grade bond market have surpassed $300 billion this year, nearly three times last year's total. Goldman Sachs estimates that AI-related capital expenditures will reach $7.6 trillion from 2026 to 2031. As companies increase bond issuance to secure investment funds, their borrowing costs are also rising.
"We are witnessing a capital-intensive corporate investment cycle that occurs once in a generation," said Lindsey Rosner, head of multi-sector bond investments at Goldman Sachs Asset Management.
While the large-scale fundraising and investment expansion reflect expectations for growth in the AI industry, they do not, in themselves, prove the economic viability of these investments. Reuters Breakingviews analyzed that while large tech companies can secure competitive advantages based on their fundraising capabilities, the critical question remains whether they can generate actual profits.
Recently, voices warning of overheating investments in the AI sector have grown alongside expectations for its growth. Delays in data center construction and declines in stock prices of AI infrastructure-related companies have raised doubts about whether the massive investments will yield corresponding profits.
Amid this backdrop, market attention is focused on the earnings reports of major memory semiconductor companies from South Korea, China, and Japan, as well as U.S. big tech firms, scheduled for this week. SK Hynix will report its third-quarter earnings on October 28, followed by Samsung Electronics on October 29, Japan's Kioxia on October 30, and China's Changxin Memory Technologies (CXMT) on October 31.
The combined market capitalization of these four major memory semiconductor companies exceeds $2 trillion. As memory semiconductors are key components in AI data centers, their earnings will indicate how much AI infrastructure investment is translating into actual semiconductor demand.
The third-quarter earnings outlook for the 'Big Four' memory firms is currently positive. Samsung Electronics previously announced that its preliminary operating profit for the third quarter reached 107.4 trillion won. SK Hynix is also expected to report an operating profit exceeding 75 trillion won for the third quarter.
Kioxia's earnings are also projected to improve significantly. According to Bloomberg, analysts expect Kioxia's operating profit for the September quarter to increase more than 20 times compared to the same period last year. CXMT also projected that its third-quarter revenue would reach between 114.7 billion and 119.7 billion yuan, with net profits estimated between 53.4 billion and 54.9 billion yuan.
However, it is difficult to assess the overall profitability of the AI industry based solely on the strong performance of memory semiconductor companies. Even if semiconductor prices and order volumes remain robust, whether big tech can recoup their investment costs through AI services is a separate issue.
In this context, investors will be looking closely at the earnings reports from U.S. big tech firms such as Alphabet, Microsoft, and Amazon this week, not only for revenue and profits but also for capital expenditure plans related to AI infrastructure and the impact of expanded investments on cash flow. The key question will be whether big tech can maintain stable profitability while continuing to make substantial expenditures.
Anthony Saglimbene, chief market strategist at Ameriprise, emphasized, "Investors need assurance that aggressive capital expenditures reflect sustainable business demand and that profitability will be maintained even after new infrastructure is operational."
* This article has been translated by AI.
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