The rapid growth of artificial intelligence (AI) has sparked debate about whether current valuations are justified or represent an unsustainable bubble. The core argument against a bubble rests on the possibility that AI breakthroughs will deliver the promised revolutionary impact: if AI systems truly solve major business and personal problems at scale, high valuations could be sustainable. However, the risk is that this doesn’t happen, potentially leading to economic consequences similar to those seen during the 2008 financial crisis.
The Parallel to the Housing Crisis
The concern isn’t simply that AI might fail to live up to expectations. Instead, the issue is that AI is becoming a dominant economic force, much like housing did before 2008. As AI investment increases, its potential impact grows. If the promised revenue and savings don’t materialize, the resulting economic shock could be self-reinforcing.
Historically, the U.S. economy absorbed shocks to the housing market. But when housing became too large a part of the economy, it became the source of wider problems. AI could follow the same path if it grows too quickly without delivering proportional returns.
Opacity in AI Financing
A key complicating factor is the lack of transparency in how AI is being financed. Much of the funding comes through private credit markets—customized, non-public loans between businesses and investors. Unlike public bonds, private credit lacks the disclosure requirements and trading transparency of traditional markets.
This opacity makes it difficult to assess the true scale of investment. While firms like Apollo may publicly state their interest in sectors like data centers, it’s hard to determine the extent of their exposure. The lack of insight into these private transactions raises concerns about systemic risk.
The Web of Interconnected Interests
The relationships between AI companies, investors, and supporting industries are complex and often unclear. This tangled web of dependencies resembles the interconnectedness that preceded the 2008 crisis, where financial institutions were deeply intertwined in risky assets. If one part of the AI ecosystem falters, the impact could ripple through the entire sector.
The potential for an AI bubble isn’t just about valuations; it’s about the systemic risk of a sector growing too quickly, financed opaquely, and becoming too central to the broader economy.
The current situation demands careful monitoring. If AI fails to deliver on its promises, the resulting economic disruption could be significant. The key takeaway is that the scale of AI’s potential impact, coupled with the opacity of its financing, warrants serious consideration.
