Anthropic Seeking $15 Billion in Debt Before Its IPO: Is That a Warning Sign or a Bullish Signal for AI Infrastructure Stocks?

The artificial intelligence industry is growing rapidly to meet historic adoption rates. To support this growth, data centers are being built as quickly as possible. "The race to scale AI has triggered one of the largest infrastructure build-outs in modern history," concludes a report by McKinsey & Co. Over the next three years alone, the firm projects more than $7 trillion will be deployed globally to scale data center infrastructure. "Whether a build-out is successful depends on many nuances, including the availability of capital and energy resources," McKinsey Co. warns. The world's current energy system is simply not designed to handle the massive influx of energy-intensive data center infrastructure expected in the coming years and decades. This has led to a surge in new energy projects, even for more speculative technologies like small modular nuclear reactors. The availability of capital, however, is a completely different challenge. In the first quarter of 2026 alone, more than $240 billion in venture funding went toward AI start-ups. That's larger than the entirety of 2025. And that figure doesn't account for public markets, through which hundreds of billions in additional capital have been raised. Now, Anthropic is looking to secure $15 billion in debt financing ahead of a potential IPO. Should the capital raise excite or worry investors? There are two things AI investors should keep in mind. Expand NASDAQ : SPCX Space Exploration Technologies Today's Change ( -1.20 %) $ -1.79 Current Price $ 147.95 Key Data Points Market Cap $2.0T Market cap calculated using publicly traded shares outstanding only. Does not include unlisted, private, or dual-class non-traded shares. Implied market cap may vary. Day's Range $ 147.32 - $ 150.85 52wk Range $ 104.83 - $ 225.64 Volume 49.1M Avg Vol 111.9M 1. The capital intensity of AI isn't going away Many skeptics have compared the current AI boom to the dot-com bubble. And while there are many similarities, the differences are critical to understand. The biggest difference, perhaps, is that during the dot-com craze, much of the critical infrastructure had yet to be built. That is, most of the world still lacked access to high-speed internet services. There was also a lack of user access points. Today, of course, high-speed internet access is nearly ubiquitous. And billions of people have an internet access point -- commonly called a smartphone -- directly in their pockets nearly all the time. That infrastructure, however, took decades to realize. The AI boom, meanwhile, already has all that critical infrastructure in place, allowing it to grow more rapidly than the dot-com era ever could. But there still is an infrastructure gap. To realize the AI industry's full potential, a massive amount of data center infrastructure will need to be built, triggering one of the biggest infrastructure build-outs in history. Without new compute power, AI growth will stall. Investors should expect capital-intensive projects for decades to come. And with many AI divisions still losing money, sizable capital raises could be the norm through the end of the decade, perhaps longer. Image source: Getty Images 2. Access to capital could become a competitive advantage If capital is necessary to scale the required data center infrastructure, access to capital could become a key competitive advantage. This is likely why so many AI companies are now seeking to go public. SpaceX (SPCX -1.20%), of course, held a record-breaking IPO in June. Now, both OpenAI and Anthropic are looking to go public. Most big tech firms, meanwhile, are already public, allowing them to tap capital markets more easily than their private peers. Scaling compute power will be critical to scaling the capacities of AI technology. In this way, investors should expect heavy competitive advantages for two types of businesses: those that are already profitable, reducing their reliance on capital markets, and those with high valuations and easy access to capital raises, such as firms that are already public. Therefore, large, profitable, public AI companies may have the strongest competitive advantages long term.