Bridgewater Warns Big Tech External Funding for AI Is Dangerous

Bridgewater Associates on Monday flagged a growing danger in the AI investment boom, saying that major technology firms are increasingly relying on external capital to fund sprawling infrastructure and research costs that in many cases outpace internal cash generation. The warning, reported by Reuters on December 15 and attributed to Greg Jensen, Bridgewater’s co chief investment officer, says the trend could presage a market bubble.

Jensen wrote that “going forward, there is a reasonable probability that we will soon find ourselves in a bubble,” and characterized the current phase of AI spending as “dangerous.” The note and subsequent republications by several outlets framed the issue around a simple accounting mechanism. As firms scale computing capacity, specialized chips, and data center footprints to support generative AI and other advanced models, the costs of deployment and scaling have surged. Where those costs exceed cash flow from operations, companies are turning to equity sales, debt issuance, or other external financing to bridge the gap.

That dynamic has caught investors’ attention. Market participants are reported to be questioning whether the pace and scale of capital expenditures are sustainable and whether an extended period of external funding could erode returns on invested capital. Critics cited in the coverage say the fallout from a failed AI investment cycle could be severe if spending does not translate into higher margins or durable revenue streams.

Bridgewater’s note stops short of naming individual companies or quantifying an aggregate capital shortfall, leaving the precise scale of the risk undefined. Still, the warning is notable because it comes from the world’s largest hedge fund and because it maps onto observable market behavior. Over the past several years, Big Tech has been a dominant force in corporate capital deployment globally, and shifts in how those firms finance growth can ripple through equity valuations, bank lending, and the broader technology supply chain.

The potential market implications are twofold. First, increased reliance on outside capital tends to raise leverage and dilute returns when investments perform below expectations. Second, a sector wide reassessment of AI project economics could trigger broad valuation adjustments among technology stocks, and spill over into suppliers such as chip manufacturers and cloud infrastructure providers that depend on large scale customer commitments.

Policy makers and regulators may take an interest if external funding becomes a systemic channel of risk. Greater use of debt or structured financing for AI projects could prompt closer scrutiny of corporate disclosures about AI related capital expenditures, and of bank and non bank lenders that underwrite large technology financings. For investors, the immediate takeaway is to demand clearer numbers on capital expenditures, expected time to payback, and the contribution of AI projects to free cash flow.

The Bridgewater note as reported by Reuters therefore serves as both a market signal and a call for more granular data. Confirming Jensen’s full text and securing comment from major technology firms about their funding strategies will be essential to measure whether this is a temporary financing pattern or the start of a broader correction in the economics of the AI boom.