Analyst: NVIDIA is Emerging as an AI Era 'Capital Allocator,' Driving Industrial Financialization

BlockBeats News, July 24th - Analyst Rick stated that NVIDIA is playing a role similar to a "central bank" in the AI era. Although NVIDIA cannot issue currency or determine interest rates, it is influencing the direction of capital allocation, the most scarce resource in the AI industry.

He pointed out that the AI industry is gradually transitioning from the traditional semiconductor supply chain to an infrastructure asset system, where capital itself is becoming an important part of the AI ecosystem. In this process, NVIDIA is locking down core production capacities such as GPUs, HBM, advanced packaging, and helping customers and suppliers solve financing issues, driving the overall industry's capital flywheel.

Currently, the AI industry has formed a cycle of "financing to purchase GPUs → renting out GPUs to generate cash flow → cash flow supporting new financing → continuing to purchase GPUs," allowing GPUs to gradually acquire infrastructure asset attributes. They can generate long-term cash flow, support collateralized financing, and even asset securitization.

At the same time, tech giants such as Microsoft, Google, Meta, and Amazon are continuously expanding AI capital expenditures, NeoCloud enterprises are expanding through debt financing, HBM suppliers and advanced packaging manufacturers are accelerating production expansion, private credit funds, infrastructure funds, and sovereign wealth funds are also entering the AI data center investment field.

Analysts believe that as the scale of AI infrastructure investments grows, the AI industry may become one of the world's largest capital absorption areas. Future AI capital expenditures in the hundreds of billions of dollars will continue to flow to GPUs, data centers, power, fiber optics, cooling systems, HBM, advanced packaging, and other sectors.

This trend may also impact the financial market structure: even if short-term interest rates fall, long-term financing costs may remain high due to strong AI capital demand. At the same time, funds will further concentrate on AI companies with stable cash flows and high growth certainty, while funding pressure in traditional industries may further increase.