Are We in an AI Bubble? Parallels With the 1929 Crash and the Dot-Com Boom Bust

The U.S. stock market is at record highs, and artificial intelligence (AI) has become the driving force behind the surge. According to the Financial Times, nearly 80 percent of market gains this year can be traced to one sector: AI. Tech giants like Nvidia, Microsoft, and Alphabet have seen their valuations soar as investors bet big on the transformative power of machine learning and automation. But as investor euphoria reaches fever pitch, some experts are asking whether history is repeating itself. Could today’s AI boom turn into tomorrow’s crash?

The situation bears striking resemblance to two of the most infamous speculative periods in financial history—the 1929 stock market crash that triggered the Great Depression and the 1999 dot-com bubble that wiped out trillions in market value. Both were marked by excitement over groundbreaking technologies that promised to reshape the world, only to give way to panic when expectations far outpaced reality. While today’s tech leaders are far more profitable and diversified than the startups of 1999—or the leveraged speculators of 1929—analysts warn that the mix of hype, overconfidence, and concentrated market dominance could still set the stage for a painful correction.

As AI reshapes industries and fuels record profits, the question remains: are we witnessing the next great technological revolution—or simply another boom poised to bust?

Few are better positioned to answer that question than Andrew Ross Sorkin, New York Times columnist and author of the new book 1929: Inside the Greatest Crash in Wall Street History and How It Shattered a Nation. Speaking in an interview about the lessons from 1929, Sorkin said he sees striking similarities between the current AI-fueled rally and the exuberance that preceded the Great Depression.

Andrew Ross Sorkin is a renowned financial journalist, author, and television anchor best known for his deep analysis of Wall Street and global markets. A New York Times columnist and founder of DealBook, Sorkin also co-anchors CNBC’s Squawk Box. He gained international recognition for his bestselling book Too Big to Fail, a definitive account of the 2008 financial crisis, later adapted into an HBO film.

Echoes of the Past

The current surge in artificial intelligence investment has drawn striking comparisons to past market manias, particularly the 1929 Wall Street crash and the 1999 dot-com bubble. In both eras, revolutionary technologies—radio and automobiles in the 1920s, the internet in the late 1990s—fueled euphoria and speculation far beyond sustainable levels. Similarly, today’s AI boom has driven massive valuations and corporate spending, often ahead of proven profitability. As Andrew Ross Sorkin and other analysts note, history suggests that innovation can inspire progress—but when excitement outpaces fundamentals, markets risk repeating the same cycles of overconfidence and correction.

“When I began writing this book eight years ago, I didn’t expect to see such clear parallels in real time,” Sorkin said. “The amount of euphoria that existed in the 1920s feels very similar to what we’re seeing today with AI.”

In 1929, the technologies captivating investors were automobiles and radio — “radio was the Nvidia of its time,” Sorkin noted. “It was a meme stock before meme stocks existed.” The common thread between eras, he explained, is leverage — how much investors and corporations are borrowing to fuel growth.

“Today, many companies are making massive, often unprofitable commitments to buy chips and expand AI capabilities,” he said. “The question is how sustainable that is. At what point do these obligations become unmanageable?”

The Long Life of a Bubble

Market bubbles, Sorkin cautioned, can persist longer than skeptics expect. “In 1996, Alan Greenspan warned of ‘irrational exuberance,’ but the market kept rising for another four years,” he said. “In 1928, Charles Merrill told clients to get out of the market — and between then and September 1929, stocks rose 90 percent.”

“There will be a correction at some point,” Sorkin added. “The question is when, and how deep. Hopefully, whatever happens looks more like 1999 than 1929.”

Sorkin emphasized that today’s markets are structurally stronger. Regulations introduced after the Depression — including the creation of the SEC and bank capital requirements — have reduced the risk of unchecked speculation. But one new danger stands out: record government debt.

“In 1929, the U.S. had a budget surplus. Today, we’re carrying enormous debt,” he said. “If a crash comes, our usual solution is to inject liquidity — but how much longer will bondholders tolerate that?”

The 1929 or the 1999 dot-com bubble was fueled largely by speculation, with many startups boasting lofty valuations despite having no real products, revenue, or customer base. Investors poured billions into companies that existed mostly on paper, driven by the promise of the internet’s future rather than its proven value. Today’s AI boom, while still exuberant, is fundamentally different: the driving forces are established tech giants like Google, Microsoft, and Amazon—companies with billions of users, profitable businesses, and real products. Their massive investments in AI infrastructure and applications reflect genuine demand and capability, though some analysts warn that even solid foundations can’t entirely shield markets from speculative excess.

The Energy Factor

While AI leaders like Google, Meta, and Amazon have vast cash reserves and aren’t heavily leveraged, Sorkin noted that the industry faces another constraint: energy. “Even with their financial strength, these companies can’t expand endlessly,” he said. “They’re running into physical limits — there isn’t enough power to run all these new data centers.”

Energy and real estate companies, meanwhile, are borrowing heavily to meet demand for AI infrastructure. Compounding the risk, Sorkin explained, is the short lifespan of chips themselves. “Unlike fiber optic cables in the 1990s, chips depreciate fast. After three or four years, they need to be replaced,” he said. “That changes the economics entirely.”

Human Nature and Market Cycles

Asked whether investors have truly learned from history, Sorkin offered a sobering reminder of human nature’s consistency. “We are all human — and we are exactly the same,” he said. “Every boom is fueled by the belief that this time is different. And every crash reminds us that it’s not.”

But Sorkin also believes that awareness of history can serve as a powerful safeguard. “Markets will always move in cycles,” he said. “What changes is how prepared we are to recognize the signs — the overconfidence, the leverage, the sense of invincibility — before they spiral out of control.”

In his view, humility and discipline are the antidotes to euphoria. “When people seem absolutely certain they’re right,” he said, “that’s usually when they’re not.” He argues that the lessons of 1929 — unchecked speculation, blind faith in new technologies, and the illusion of endless growth — are resurfacing today in the excitement surrounding artificial intelligence.

As the AI revolution accelerates, Sorkin’s message is both cautionary and timeless: technological progress may reshape industries and fortunes, but it doesn’t rewrite human psychology. Booms and busts will continue as long as optimism outpaces reality — and the smartest investors, he suggests, are those who remember that even in an age of algorithms, emotion still drives the market.

Sources: AirGuide Business airguide.info, bing.com, cnn.com, 1929: Inside the Greatest Crash in Wall Street History