In recent years, the global technology sector has been electrified by the promise of artificial intelligence (AI). Billions are pouring into AI companies, governments are scrambling to regulate and leverage its power, and tech giants dominate financial markets at levels never seen before. Yet, the feverish excitement surrounding AI bears striking resemblance to a technology revolution—and bust—that shaped the twentieth century: the electrification boom of the 1920s. History shows that while such transformative innovations can drive extraordinary progress, unchecked speculative exuberance and weak regulatory frameworks can also bring ruin. As AI weaves itself into the fabric of economies and societies worldwide, examining the lessons of the past has never been more crucial.

The Electrification Boom: A Parallel to Today’s AI Craze

One hundred years ago, electricity was the cutting-edge “high tech” that promised to unlock new industries, revolutionize communication, and change daily life on a global scale. Investors flocked to companies like General Electric, Electric Bond & Share, Commonwealth Edison, and the Radio Corporation of America (RCA). Electrification enabled new products—radios, electric appliances, movie theaters—and heralded a new consumer age powered by automation and convenience. Social and economic life adapted quickly as homes and factories electrified, and world leaders such as Vladimir Lenin declared broad electrification a path to modernity and power.

Fast forward to the present: AI is the modern equivalent of electricity as a general-purpose technology. Companies across every sector strive to integrate machine learning, computer vision, and generative AI tools into their business models and operations. The industry’s market value is rising at a blistering pace—Goldman Sachs predicts AI could add $7 trillion to the global economy over the next decade, while market analysts estimate the AI sector alone could surpass $1.8 trillion by 2030. Tech giants like Microsoft, Nvidia, Alphabet (Google), Apple, Amazon, and Meta increasingly dominate stock indices. In June 2024, Nvidia briefly became the world’s most valuable company by market capitalization, fueled largely by its AI leadership.

The Peak: When Technology Drives Market Frenzy

In the late 1920s, electrification companies reached astonishing valuations, often detached from underlying business fundamentals. The sector attracted not only industrial investments but also swept up ordinary households via stocks, bonds, and newly invented mutual funds. Investment trusts—sometimes little more than speculative vehicles masking real risk—became rampant, echoing today’s proliferation of AI-themed exchange-traded funds (ETFs).

History repeats: just as electrification underpinned many of the megacap companies of the 1920s, AI now forms the bedrock of global tech dominance. The so-called “Magnificent Seven” (Apple, Microsoft, Alphabet, Amazon, Meta, Nvidia, and Tesla) collectively account for over a third of the S&P 500’s market capitalization, with AI at the heart of their strategies. This concentration of market power has drawn both praise for driving innovation and concern over systemic risk.

The similarities don’t end at concentration. Both in the 1920s and today, regulatory frameworks have struggled to keep pace with technological change. The Dow Jones launched the Utilities Average in 1929 to reflect the modern economy, just as AI is now reshaping major stock indices and the makeup of passive investment portfolios worldwide.

The Bust: When Hype Outpaces Reality

The electrification boom ended abruptly. On October 24, 1929 (“Black Thursday”), cracks in speculative excess triggered the Wall Street Crash that led to the Great Depression. The Dow Jones Utilities Average plummeted from 144 in 1929 to just 17 by 1934. The consequences were dire: US unemployment soared to 25%, millions lost their savings, and the promised prosperity from electrification gave way to breadlines and social hardship.

The collapse also exposed deep systemic weaknesses. Complex corporate structures, market manipulation, and lack of oversight lay at the heart of the crisis. Executives like Samuel Insull—who built multi-billion dollar utility empires—became the focus of fraud investigations. Over 600,000 shareholders and 500,000 bondholders were wiped out with Insull’s bankruptcy. In the aftermath, sweeping regulatory reforms ensued. The Public Utility Holding Company Act of 1935 broke up conglomerates and established new industry standards, while utilities were eventually recast as stable, regulated infrastructure.

Today’s AI sector, while not facing imminent collapse, shows some classic hallmarks of a bubble: extraordinary capital inflows, opaque risk exposures, and valuations hard to justify compared to economic fundamentals. The shockwaves of the 2022-2023 tech downturn—when some AI stocks dropped by over 50%—offered a taste of potential volatility. With an estimated $350 billion being invested in generative AI startups according to McKinsey’s 2024 Tech Report, calls for caution have grown louder.

AI in 2024: Regulation, Risk, and Reinvention

No technology exists in a vacuum. Just as electrification led to both unprecedented progress and catastrophic busts, AI’s world-changing impact carries systemic risk. Regulators are only beginning to respond. The European Union passed the world’s first sweeping AI Act in March 2024, aiming to establish clear rules for development, deployment, and accountability. Meanwhile, US regulatory policy remains fractured: Federal proposals to “cut red tape” on AI contrast with more robust efforts in California, New York, and Illinois to safeguard jobs, privacy, and intellectual property. The disconnect between federal and local directives recalls the patchwork reform attempts of the 1930s.

For investors, the lessons are both cautionary and pragmatic. Exposure to AI is more pervasive than most realize—through retirement portfolios, index funds, and pension plans—raising the risk of widespread market contagion should sentiment shift. The AI sector is also attracting increasing scrutiny for potential speculative excess—market concentration, the reliability of “moonshot” business models, and the challenge of validating new technological threats from deepfakes to bias and data misuse.

Conclusion: Can AI Avoid the Fate of Electrification’s Bust?

AI is set to become the invisible infrastructure of the digital age, much like electricity did a century ago. The question is whether society, regulators, and the investment community can learn from history. The electrification boom brought enduring social and economic advancement—but only after devastating losses forced a systemic reset and new guardrails for innovation.

In 2024, scholars, watchdogs, and policymakers urge that the time to act is now. Ensuring robust, forward-looking regulation and market transparency may be the only way to secure the benefits of AI while sidestepping the historic pitfalls of unchecked technological exuberance. As finance and industry race toward an AI-powered future, the lessons of both the Roaring Twenties and the Great Depression—innovation must ultimately serve the wider public good—must not be forgotten.