Silicon Valley can't hold on any longer, shaking Wall Street, the "AI arms race" begins to spread, and risks are also present!

The AI "Arms Race" Among Tech Giants is Evolving into a Complex Financial Game.

As annual capital expenditures easily reach hundreds of billions of dollars, even Amazon, Google, Meta, Microsoft, and Oracle, with cash reserves exceeding $340 billion, are beginning to feel unprecedented financial pressure.

They are breaking away from the traditional reliance on self-funding for infrastructure development and are turning to Wall Street for more complex financial solutions, attempting to provide ammunition for this expensive race without compromising their financial stability, while risks are also on the rise.

The "Sweet Burden" of Trillion-Dollar Giants: AI Infrastructure Costs Drive Financing Innovation

In the past, tech giants were accustomed to using their massive internal cash flows to build data centers, but the rise of AI has completely changed the rules of the game.

The speed and scale of this competition have forced them to seek external capital. Investors and credit rating agencies are closely watching how these tech giants will pay for AI data centers and whether these massive investments can be converted into new revenue.

To maintain healthy financial statements while aggressively expanding, tech giants are beginning to collaborate with bankers to design increasingly complex financial strategies, with a core goal of transferring some costs and risks off their balance sheets.

In this context, financial instruments such as joint ventures, backstop agreements, and syndicated debt, which were rarely heard of in the tech circle before, are now being brought to the table.

Three Financial "Plays" for Risk Sharing

In the exploration of "externalizing" risks and costs, three innovative financial "plays" have emerged, all cleverly externalizing risks and liabilities.

1. Meta's "Off-Balance Sheet" Strategy: Joint Ventures

Meta initiated a financing of up to $29 billion for its data center project named "Hyperion" in Louisiana.

The core structure involves establishing a joint venture with investment firm Blue Owl Capital. Blue Owl is investing $3 billion in equity, while the project's required $26 billion in debt is being syndicated by bond giant Pimco with the assistance of Morgan Stanley.

The key to this structure is that Meta will repay the debt in the form of lease payments in the future, thereby moving the entire project off its balance sheet and controlling debt levels.

2. Oracle's "Risk Sharing": Syndicated Loans

As the world's fourth-largest cloud service provider, Oracle recently agreed to become a tenant of a 1.4GW data center complex being developed by Vantage Data Centers, one of the largest projects under construction globally.

Due to the project's massive scale, developer Vantage is collaborating with six banks led by JP Morgan and Japan's Mitsubishi UFJ Financial Group, including Goldman Sachs, to syndicate the $22 billion in debt required for the project This model reduces the risk exposure of individual institutions by distributing risk among multiple lenders, making large-scale financing possible.

3. Google's "Clever Design": Contingent Guarantees

Google's plan is the most complex and sophisticated, involving "contingent guarantees."

In this transaction, Google provided up to $3.2 billion in contingent guarantees for the leasing contract between cloud startup Fluidstack and data center owner TeraWulf, thereby acquiring a 14% stake in TeraWulf.

The clever design lies in the fact that this guarantee is classified as a "contingent liability," which will only be triggered in the event of Fluidstack's default, meaning Google is unlikely to have to account for it as a current liability.

With Google's support, TeraWulf raised $1 billion last month through convertible bonds underwritten by Morgan Stanley and Cantor Fitzgerald, more than double its initial financing target.

TeraWulf's Chief Financial Officer stated at a meeting last month:

"It's not easy to get a $2 trillion company, their management team, board, and everyone to agree on a novel concept, but I hope we have provided a roadmap."

Concerns Amidst Enthusiasm: Overheating, Concentration, and Leverage Risks

The enormous financing needs of tech giants coincided with a credit market flooded with cash.

Private credit funds holding hundreds of billions of dollars ready to invest, along with banks increasingly comfortable with projects that have "investment-grade" tenants, are actively pouring in. The loan-to-total-cost ratio for data center projects has significantly increased compared to the past.

Jason Tofsky, Global Head of Digital Infrastructure Banking at Goldman Sachs, stated that lenders are agreeing to provide 80% to 90% of the total costs for data center projects. According to data from real estate firm JLL, lenders for data centers typically cover 65% to 80% of the total costs for newly developed projects. Tofsky remarked:

"There is enough capital in the market to fund projects that are well-known in the market. The market can digest these projects well."

However, the frenzy of capital is giving rise to new risks.

First is the risk of market overheating. Analysts at UBS warned in a report last month that the influx of private credit into the data center sector, while promoting AI development, could also "increase the risk of market overheating."

Second is the risk of high concentration. Leasing contracts for data centers are highly concentrated among a few creditworthy tech giants. This raises concerns: if any of these companies cut spending due to strategic adjustments or face a hit to their credit ratings, the entire ecosystem could be at significant risk.

Finally, some companies' leverage risks have already become apparent. Credit rating agencies Moody's and S&P issued warnings to Oracle in July, pointing out that its leverage ratio (currently at 4.3 times) is far higher than that of other "hyperscale" providers as it enters the AI infrastructure construction phase. If it does not reduce its debt-to-earnings ratio to below 3.5 times, its credit rating could face a downgrade risk Moody's analysts wrote in a credit report:

"Although several other large-scale providers are building artificial intelligence infrastructure, none have entered this phase with leverage as high and cash flow as negative as Oracle."