Today’s AI Hype Has Echoes of a Devastating Technology Boom and Bust 100 Years Ago
By Cameron Shackell, Queensland University of Technology
Published October 7, 2025
As excitement around artificial intelligence (AI) reaches fever pitch in 2025, experts are drawing striking parallels between today’s AI boom and the electrification frenzy of the 1920s—a period that culminated in one of the most catastrophic economic collapses in history. Understanding this century-old episode offers valuable lessons for navigating today’s rapidly evolving AI landscape and its potential pitfalls.
The Electrification Boom: A Transformative Technology Ignites Public and Investor Enthusiasm
A hundred years ago, electricity was the defining “general purpose technology” of the era, much like AI is today. The 1920s witnessed a surge of investment and innovation around electrical infrastructure and applications, creating profound social and economic change. The United States emerged as an industrial powerhouse, with new technologies promising automation, increased productivity, and a future filled with leisure and consumer goods.
Investors eagerly poured capital into electric utilities such as Electric Bond & Share and Commonwealth Edison, alongside emerging companies leveraging electricity in novel ways, including General Electric, AT&T, and RCA. The public was captivated by new experiences like modern movies, radio broadcasts, and faster printing presses. The excitement was so widespread that Soviet leader Vladimir Lenin famously declared, “Communism is Soviet power plus the electrification of the whole country,” reflecting the era’s faith in electricity’s revolutionary potential.
The Market Peak: Overenthusiasm and Complex Financial Structures Hint at Trouble
By the late 1920s, electricity stocks had become a favorite among investors, despite the difficulty in assessing their true financial health. A small number of holding companies controlled approximately 80% of the electricity supply market, often using convoluted ownership structures to bypass regulations and sell shares under different names. This consolidation mirrored the massive influence today’s tech giants have over the AI ecosystem.
In September 1929, utilities accounted for nearly 18% of the New York Stock Exchange, and the Dow Jones introduced the electricity-heavy Utilities Average, underscoring the sector’s importance. Similarly, in 2025, tech companies linked to AI make up over a third of the S&P 500 and nearly three-quarters of the NASDAQ, highlighting the profound influence of transformative technologies on modern markets.
The Bust: From Boom to Crash and a Decade of Global Hardship
Despite the promise, the electrification boom ended in disaster. The Dow Jones Utilities Average plummeted from a high of 144 in 1929 to just 17 by 1934. The infamous “Great Crash” of October 1929 was the tipping point, triggering widespread bank failures, a credit collapse, and a precipitous decline in industrial production.
Unemployment in the U.S. soared from around 3% to 25% by 1933, with many countries heavily dependent on international trade, including Germany, Australia, Chile, and Canada, experiencing similarly severe economic distress. The era of shorter working hours and electric-powered leisure devolved into a grim reality marked by soup kitchens and bread lines.
Key figures from the electrification era also faced fallout. Samuel Insull, once a titan of the electric utility industry and former protégé of Thomas Edison, was at one stage worth an estimated $150 million. Following the collapse of his empire in 1932, he faced charges of embezzlement and larceny but was ultimately acquitted; nonetheless, hundreds of thousands of shareholders and bondholders lost their investments. Some see Insull more as a scapegoat than a criminal mastermind, pointing to systemic flaws that the crisis exposed.
Regulatory Reform: From Boom to Busted to Regulated Infrastructure
The shockwaves of the crash led to sweeping regulatory reforms, including the Public Utility Holding Company Act of 1935, which dismantled massive holding companies and imposed geographical limits on utility operations. The vibrant electricity sector transitioned into regulated, “boring” infrastructure—a transformation symbolized by the Electric Company square in the 1935 edition of the Monopoly board game.
Lessons for the AI Era
Today’s AI industry is evolving rapidly, with a small number of interconnected firms creating the core infrastructure. Much like the 1920s investors pouring money into electric utilities and related companies, modern investors are heavily exposed to AI stocks, often unknowingly through their superannuation funds or exchange-traded funds (ETFs).
Regulation of AI remains fragmented and generally lax, reminiscent of the laissez-faire environment before the 1929 crash. While the European Union is leading with pioneering AI legislation aimed at stricter oversight, some nations like the United States have taken the opposite stance by reducing regulatory burdens on AI development. Meanwhile, individual U.S. states are experimenting with their own legal responses, and courts struggle to interpret outdated laws in the context of emerging technology.
Whether AI will follow electricity’s trajectory—moving from a speculative boom to becoming invisible infrastructure after a painful reckoning—remains uncertain. However, as history illustrates, ignoring these parallels increases the risk of a similar bust with deep economic and social consequences.
Conclusion
The electrification boom and bust of the 1920s provide a cautionary tale as the world stands on the brink of an AI-driven transformation. Recognizing the signs of overhyped markets, concentrated company power, and inadequate regulation is critical to steering AI towards sustainable growth and avoiding the devastating fallout that history warns can follow unchecked technological exuberance.
For more insights into technology, economy, and history, visit The Conversation.
Disclosure: Cameron Shackell is a sessional academic at Queensland University of Technology and CEO of Equate IT Consulting, a firm specializing in AI analytics.
