AI sector’s circular investments spark dot-com bubble fears

The intricate financial maneuvers within the burgeoning artificial intelligence sector are raising concerns among analysts, who point to a pattern of mutual investments and subsidies between AI infrastructure providers and their customers. This circular dynamic, reminiscent of the dot-com bubble’s pitfalls, could be artificially inflating demand and creating systemic risks.

### Intertwined Valuations and Potential for Systemic Risk

A notable trend involves AI infrastructure leaders, such as Nvidia, investing directly in their clients, who subsequently increase their purchases of these providers’ products. Conversely, customers of infrastructure like OpenAI are also seen investing in their suppliers. This interconnectedness has led to soaring valuations for major technology companies, particularly as stock prices react positively to news of such deals. Experts caution that this close coupling of fates means a setback for one company could have cascading negative effects across the entire ecosystem, a dynamic observed during past technological booms.

### Echoes of the Dot-Com Bust

The current situation draws parallels to the late 1990s and early 2000s dot-com bubble. During that era, internet service providers (ISPs), facing cash flow challenges, were financed by their equipment suppliers through loans and equity stakes. These suppliers, including prominent names like Cisco Systems, Nortel Networks, and Lucent, extended billions to ISPs. While on the surface this indicated robust business activity, it masked underlying financial fragility. When capital markets tightened, many ISPs collapsed, leaving equipment vendors with significant write-offs and exacerbating the tech market’s downturn.

While the current AI landscape differs – with many major tech companies possessing stronger profit margins and primarily utilizing internal cash flows for capital expenditures – some analysts see nascent warning signs. For instance, Oracle recently raised a substantial $18 billion in debt, indicating a potential shift in funding strategies as companies scale up AI operations.

### Concerns Over OpenAI’s Profitability and Leverage

A primary concern centers on the dependency on the success of entities like OpenAI. As the developer of ChatGPT, OpenAI has yet to achieve profitability. Analysts express apprehension about the company’s ability to meet its revenue projections and the potential consequences should it fail to do so. This reliance on a single, unproven entity creates a concentration of risk within the AI ecosystem. Furthermore, recent agreements where companies like OpenAI and CoreWeave take on debt while simultaneously receiving investments from Nvidia are particularly worrying. This practice of leveraging capital for further investment can be seen as an unhealthy signal, suggesting that customers may not be able to afford necessary infrastructure without taking on significant financial obligations.

### Diverse Perspectives on AI Investment Strategies

Despite these concerns, some on Wall Street view these strategic partnerships as beneficial. Proponents argue that such alliances facilitate the rapid deployment of capital required for AI infrastructure development, potentially accelerating the realization of substantial returns on massive investments. Bernstein analyst Stacy Rasgon, for example, has suggested that Nvidia’s investments in its customers represent a highly effective use of its capital, and does not believe the market is close to bubble territory. Nvidia CEO Jensen Huang has also defended such deals, likening OpenAI to a potential “multitrillion-dollar hyperscale company” and expressing regret for not investing more heavily in the company’s early stages. These differing viewpoints highlight the complexity and ongoing debate surrounding the financial structures underpinning the AI revolution.