How do investors keep track of which companies will benefit from the AI boom and which may face serious challenges because of it? The answer, at least for some, is with Excel.
The artificial intelligence revolution has been fueled by the deep pockets of tech giants, but a new warning from Bank of America suggests that model is cracking under the weight of massive data center buildouts. In September and October alone, companies like Meta, Oracle, Amazon, and Microsoft borrowed $75 billion through bonds and loans for AI infrastructure.
That figure more than doubles the annual average of the past decade. And that reveals a fundamental shift in how the industry finances its ambitions.
The numbers tell a stark story. Yahoo Finance reports that AI capital expenditures are projected to consume 94 percent of operating cash flow minus dividends and share repurchases in 2025 and 2026, up from 76 percent just a year ago. Even the strongest cash flows from cloud services and advertising can no longer keep pace with the scale of investment required. Global data center spending could reach $3 trillion by 2028, with a significant portion financed through external borrowing. Companies are increasingly turning to debt markets, securitization, and complex financial instruments to maintain momentum.
We analyzed social commentary surrounding this story. The main takeaway? Skepticism. Commenters raised concerns about whether this represents another tech bubble in the making, with some questioning whether AI capabilities justify the enormous spending spree. And Michael Burry made his thoughts on a potential AI bubble known too.
Others, investors and commentators, expressed their worries about disappointing returns on investment and the sustainability of current valuations. The debate reflects genuine uncertainty about whether the promised AI revolution will deliver returns commensurate with the debt being accumulated.
But there’s more to consider. Companies with strong balance sheets like Meta, which holds over $60 billion in cash reserves against $37 billion in debt, appear better positioned to weather potential downturns. Nvidia exemplifies resilience with minimal debt and massive free cash flows from chip sales.
Smaller players like Advanced Micro Devices face steeper challenges, potentially borrowing at higher rates due to lower credit ratings. Oracle’s nearly $96 billion debt load raises particular concerns about interest coverage if economic conditions deteriorate.
So how do investors evaluate the situation? What can a private investor, someone without access to a Bloomberg terminal, track a company’s debt and formulate an informed position about a stock?
One way is with investment spreadsheets in Excel or Google Sheets. It doesn’t take much time to build one, and it allows investors to keep their own notes and analysis on their private hard drives, ready for evaluation or changes at any point.
Building your own system for tracking debt, pulled from public reporting, could be the key. Scraping data from public reports, ingesting it into a spreadsheet, then using that to build a visual dashboard could be a major (and free) asset to many investors.
So, yes. The AI boom is likely to continue, but not all players will succeed equally. The winners will be those that can thread the needle between aggressive growth and financial prudence. Those who can spot the winners may be rewarded.
And companies that fail to generate profitable returns on their massive infrastructure investments risk seeing debt become a burden rather than a tool for expansion. The next few years will reveal whether today’s AI spending represents visionary infrastructure building or another chapter in tech’s cyclical boom-and-bust history.