A recent Wall Street Journal analysis warns that despite massive AI investments, Big Tech is showing signs of financial stress. Companies like Microsoft, Alphabet (Google), and Amazon have together spent over $600 billion on AI since 2023—and are projected to hit $1 trillion by 2026. While these firms entered the boom with strong balance sheets, the rapid shift toward capital-intensive AI infrastructure is eroding their cash reserves and altering how their businesses operate.
The report highlights a structural transformation: Big Tech is evolving from a predominantly scalable, high-margin software and cloud business model into something more akin to a capital-intensive industrial enterprise—similar to semiconductor manufacturers. This means they are exposed to risks such as underutilized data-centers or obsolescence if AI demand slows.
Financial indicators are already reflecting strain. According to the WSJ, Microsoft’s cash and liquid assets have fallen significantly as a percentage of total assets, while Alphabet and Amazon are grappling with shrinking free cash flow. At the same time, some companies are taking on more debt to sustain their AI build-out: for example, Meta and Oracle have both issued large bond offerings tied to AI infrastructure ambitions.
For investors, this suggests a need to rethink valuation metrics. Traditional measures like margins and cash flow may no longer fully capture Big Tech’s AI-driven risks. Instead, analysts are increasingly paying attention to AI-specific metrics—such as the growth in AI users or long-term revenue commitments—to assess how these companies will perform in a landscape where infrastructure costs are now front and center.
