THE LONG VIEW

William H. Janeway

As investment in AI surges and valuations soar, a growing body of evidence suggests that financial speculation is outpacing productivity gains.

N RECENT WEEKS, THE NOTION THAT WE ARE WITNESSING AN“ AI BUBble” has moved from the fringes of public debate to the mainstream. As Financial Times commentator Katie Martin aptly put it,“ Bubble-talk is breaking out everywhere.”

The debate is fueled by a surge of investment in data centers and in the vast energy infrastructure required to train and operate the large language models( LLMs) that drive generative AI. As with previous speculative bubbles, rising investment volumes fuel soaring valuations, with both reaching historic highs across public and private markets. The so-called“ Magnificent Seven” tech giants— Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia, and Tesla— dominate the S & P 500, with each boasting a market capitalization above $ 1 trillion, and Nvidia is now the world’ s first $ 5 trillion company.

In the private market, OpenAI reportedly plans to raise $ 30 billion at a $ 500 billion valuation from SoftBank, the most exuberant investor of the post-2008 era. Notably, this fundraising round comes even as the company’ s losses totaled $ 5 billion in 2024 despite $ 3.7 billion in revenue with its cash burn expected to total $ 115 billion through 2029.

Much like previous speculative cycles, this one is marked by the emergence of creative financing mechanisms. Four centuries ago, the Dutch Tulip Mania gave rise to futures contracts on flower bulbs. The 2008 global financial crisis was fueled by exotic derivatives such as synthetic collateralized debt obligations and credit default swaps. Today, a similar dynamic is playing out in the circular financing loop that links chipmakers( Nvidia, AMD), cloud providers( Microsoft, CoreWeave, Oracle), and LLM developers like OpenAI.

From railroads to electrification to the internet, waves of financial speculation have repeatedly mobilized vast quantities of capital to fund potentially transformational technologies whose returns could not be known in advance.

While the contours of an AI bubble are hard to miss, its actual impact will depend on whether it spills over from financial markets into the broader economy. How— and whether— that shift will occur remains unclear. Virtually every day brings announcements of new multibillion-dollar AI infrastructure projects. At the same time, a growing body of reports indicates that AI’ s business applications are delivering disappointing returns, indicating that the hype may be running well ahead of reality.

The Ghosts Of Bubbles Past

Financial bubbles can be understood in terms of their focus and locus. The first concerns what investors are betting on: Do the assets that attract speculation have the potential to boost economic productivity when deployed at scale? Second, is this activity concentrated primarily in equity or credit markets? It is debt-financed speculation that leads to economic disaster when a bubble inevitably bursts. As Moritz Schularick and Alan M. Taylor have shown, leverage-fueled bubbles have repeatedly triggered financial crises over the past century and a half.

The credit bubble of 2004-07, which focused on real estate and culminated in the global financial crisis of 2008-09, is a case in point. It offered no promise of increased productivity, and when it burst, the economic consequences were horrendous, prompting unprecedented public underwriting of private losses, principally by the U. S. Federal Reserve.

DECEMBER 2025 | FINANCIAL ADVISOR MAGAZINE | 21