AI Boom Raises Familiar Risks of Speculative Bubbles
- Massive AI investment echoes past tech bubbles, promising innovation but risking financial fallout if expectations fail to materialize.
Tech Optimism Meets Historical Caution
Leading figures in the tech industry acknowledge that artificial intelligence is driving a speculative boom. Sam Altman of OpenAI and Amazon founder Jeff Bezos both concede that while AI may yield long-term benefits, many investors are likely to incur substantial losses. The enthusiasm surrounding AI has led to funding for both promising and questionable ventures. Despite the optimism, comparisons to previous bubbles suggest caution is warranted.
The idea of a “good” bubble—one that accelerates innovation—is explored in the book Boom: Bubbles and the End of Stagnation by Byrne Hobart and Tobias Huber. The authors argue that some bubbles reflect a collective vision of a radically different future, rather than mere financial excess. Risk-taking, they suggest, is a necessary condition for technological progress. However, history shows that such periods often end in painful corrections.
Lessons from Past Technology Bubbles
Over the last 250 years, speculative manias have repeatedly reshaped economies and societies. Britain’s canal and railway booms in the 18th and 19th centuries introduced transformative infrastructure but also triggered financial crises. The U.S. railroad expansion of the late 1800s created a continental market but culminated in the Panic of 1873 and a prolonged depression. More recently, the dot-com bubble of the late 1990s led to massive losses, even as it laid the groundwork for today’s internet economy.
Amazon survived the dot-com crash, though its stock fell over 90% before recovering. Telecom failures like WorldCom were common, yet the fiber-optic networks built during the boom enabled platforms such as YouTube and Netflix. Among all innovation-driven bubbles, the internet era was followed by the mildest downturn, thanks to aggressive monetary and fiscal interventions. Still, those same policies contributed to the housing and credit bubbles that led to the 2008 financial crisis.
AI’s Unique Risks and Uncertain Outcomes
Unlike previous technologies, artificial general intelligence remains largely unproven. The current wave of investment is a multi-trillion-dollar experiment aimed at replicating human reasoning in machines. If unsuccessful, the costs may outweigh the benefits, especially given the reliance on expensive hardware and debt-financed data centers. Unlike railways or fiber-optics, AI infrastructure may not retain long-term value if the technology fails to deliver.
Julien Garran of The MacroStrategy Partnership estimates that AI-related spending is currently boosting U.S. GDP by about 3%. However, past bubbles have ended abruptly, and today’s policymakers may have fewer tools to cushion a downturn. The U.S. government is already running a large fiscal deficit, and the Federal Reserve’s balance sheet remains inflated. Inflationary pressures further limit the scope for intervention, leaving investors exposed to significant risk.
The concept of “reality distortion fields,” popularized in tech circles, is often associated with visionary leadership. In speculative bubbles, this phenomenon extends to entire markets, where collective belief can temporarily override economic fundamentals. AI’s promise of transformative change may be fueling such a distortion, encouraging investment in ideas that lack proven viability. As history suggests, the line between visionary progress and financial overreach is often visible only in hindsight.
Our article is based on a piece by Edward Chancellor, a contributor to Breakingviews.
