Meta's ambitious AI investments and financial manoeuvres have drawn fresh scrutiny as the tech giant pursues dominance in artificial intelligence amid concerns about transparency and long-term risk. The company’s stock performance in 2025 tells a complex story: while Meta shares have risen by 5.7%, this growth substantially lags behind the S&P 500’s 15.2% gain, buoyed by AI leaders like Nvidia and Alphabet. Investors are increasingly cautious as Meta’s massive AI spending, including a $27 billion AI data centre project, has yet to generate sufficient revenue growth to justify the outlay.

At the heart of the controversy is the financing structure behind Meta’s $27 billion data centre in Richland Parish, Louisiana. Rather than owning the facility outright or recording the debt on its balance sheet, Meta is engaging in off-balance sheet borrowing through a joint venture called Hyperion, created with investment firm Blue Owl Capital. Meta holds a 20% stake while Blue Owl owns 80%. In October 2025, bonds worth $27.3 billion were issued to finance the project, primarily bought by institutional investors like Pimco.

This setup uses a Variable Interest Entity (VIE) structure, an approach that raises alarm bells among observers familiar with its notorious use by Enron prior to its collapse in 2001. Back then, VIEs were used to hide debt, inflate earnings, and obscure financial risks. Meta’s application of a VIE is coupled with lease accounting designed to classify its involvement as an operating lease, which effectively keeps the debt off Meta’s balance sheet. However, this classification is contentious: for an operating lease to apply, Meta should not control key activities of the venture, yet reports suggest Meta’s decisions and expertise will be pivotal to the joint venture’s success. Moreover, while Meta asserts it lacks power to direct the venture, it also faces obligations around absorbing losses or paying guarantees, which muddles the clarity of risk exposure.

Financial analysts caution that these accounting techniques might obscure the true financial burden Meta is undertaking. A residual value guarantee in the JV agreement means Meta could be liable for capped cash payments based on the data centre's value under certain conditions, notably if it chooses not to renew the lease after the initial term. As industry capital expenditures on AI infrastructure are projected to triple, potentially reaching $5 trillion to $7 trillion by 2030, this type of borrowing practice raises broader concerns about credit risk and financial stability in the sector.

Meta is not alone in leveraging heavy debt to fuel AI data centre construction. Since September 2025, hyperscalers like Amazon, Google, Oracle, as well as bitcoin miners pivoting to AI services such as TeraWulf and Cipher Mining, have collectively issued approximately $97 billion in AI-related bonds. The surge in AI financing is prompting credit analysts to raise the cost of capital for higher-risk players. Oracle and CoreWeave, another AI cloud computing firm, are among those experiencing increased borrowing costs. CoreWeave, notably, struck a $14.2 billion deal with Meta to supply cutting-edge computing infrastructure until 2031, intended to accelerate Meta’s AI model training capabilities.

This wave of capital raises the stakes for investors who must now carefully assess credit ratings and risk profiles among AI infrastructure providers to distinguish sustainable growth from precarious debt-fuelled expansion. Credit rating agencies and market observers suggest that only projects with sound financial structuring and reasonable cost of capital will likely endure, warning against unchecked growth driven by optimistic forecasts.

While Meta’s total AI expenditure remains staggering, with investments including a 49% stake in Scale AI for $14.3 billion and promising ongoing product spend of $450 million annually, the company is simultaneously restructuring its AI workforce. Around 600 employees have been laid off from Meta’s Superintelligence Labs in a bid to streamline operations and enhance decision-making efficiency. Despite these cuts, Meta's TBD Lab, focused on developing next-generation large language models, remains unaffected.

Investors, regulators, and market watchers need to remain vigilant regarding Meta’s financial engineering and broader AI capital trends. Anticipated increases in AI spending and the resulting debt accumulation accentuate the risk that weaker players may face deteriorating credit ratings and elevated borrowing costs. The spectre of off-balance sheet liabilities reminiscent of previous corporate scandals like Enron adds an additional layer of caution to the bullish narrative around AI’s transformative potential.

Ultimately, while Meta’s AI strategy could pioneer new business tools and online experiences, the opaque financing methods and looming credit risks call for a measured approach to buying the stock. As the AI sector matures and spending intensifies towards 2030, transparency and financial prudence may well determine who emerges as the genuine winners in this high-stakes race.

📌 Reference Map:

  • [1] (Google News) - Paragraphs 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
  • [2] (Forbes - Peter Cohan) - Paragraphs 3, 4
  • [3] (Forbes - Kirk Ogunrinde) - Paragraph 7
  • [4] (Forbes - Zachary Folk) - Paragraph 8
  • [5] (Forbes - Shivaram Rajgopal) - Paragraph 4
  • [6] (Forbes - Peter Cohan) - Paragraph 2
  • [7] (Forbes - David Jeans) - Paragraph 8

Source: Noah Wire Services