AI Boom Could Repeat Dot-Com Bust, Columnist Warns

Charles Gasparino isn’t convinced the artificial intelligence rally will end well. In a New York Post column published Oct. 17, 2026, at 8:21 p.m. ET, the veteran financial writer argues the AI market could follow the dot-com bubble’s path and leave investors with heavy losses. His warning carries weight: Gasparino remembers how that boom ended.

The Dot-Com Parallel

Gasparino bases his comparison on the late 1990s. Internet stocks—including shares in companies that weren’t earning money—went to the public as investments that could defy common sense and gravity. He calls the era’s language a “new paradigm,” a phrase he says disguised irrational exuberance, with emotion rather than metrics setting valuations. The feared Y2K crisis arrived on Jan. 1, 2000, but didn’t become the catastrophe many expected. The real threat, he writes, was already growing in the stock market.

It became clear in March 2000, when the historic run-up proved to be one of history’s great investment bubbles. Many companies at the frenzy’s center had what Gasparino calls “outright insane” business models. Most others were simply overvalued. A handful had real promise, but still had to survive the correction that followed. The losses were staggering. A generation of investors got burned, and the technology market took years to recover. Gasparino’s point isn’t that the internet was a fraud. Prices had simply run far ahead of anything resembling earnings.

Familiar Sales Pitch

He says today’s AI boom has a similar pitch: groundbreaking technology, paired with the promise that everyone can get rich. Gasparino concedes that the technology may eventually deliver. The path could be long and messy, though. Investors who bought into the story at the internet mania’s peak learned that a sound idea and a sound investment aren’t the same thing. Pets.com looms large in his account. People touted the company as a possible next Microsoft, yet the 2000 crash swept it away alongside Microsoft itself and nearly every public company tied to the internet business. Small investors, he writes, lost everything.

Gasparino admits it’s hard to pinpoint what flipped sentiment during the dot-com years—or what might trigger a similar reversal in AI. Still, he offers a theory. Hedge funds and institutions that conduct their own research, rather than relying on financial television promoters, likely sense trouble. Those investors, he argues, feel something isn’t right with AI, its underlying data, or Wall Street’s sales machine. Some have started taking profits. Gasparino also worries many investors today either don’t remember the dot-com era or ignore it while weighing AI bets.

Rates, Debt and the Coming IPOs

Recent market moves add to his unease. Rates rose after a bad inflation report, and AI stocks sold off in response. Gasparino says he can’t tell whether those moves represent the market’s final verdict on AI. More enthusiasm could still arrive. Initial public offerings from hyperscalers such as Anthropic, and possibly OpenAI, could come within weeks or months; fresh listings tend to revive the excitement that inflates bubbles.

He also ties the AI trade to the federal government’s large borrowing needs. Interest rates, he argues, will climb because AI spending competes with Washington for capital. He predicts a correction for AI and for companies adopting the technology through heavy spending, much of it funded with debt. His advice to investors is blunt. Take profits. Avoid greed. Don’t count on the company you back surviving a crash. Gasparino’s column reminds readers that the last generation of tech investors paid a steep price for hope.

Why This Matters: The stakes reach well beyond Wall Street trading desks. Gasparino’s argument centers on debt-funded spending, rising interest rates, and the strain heavy federal borrowing places on private capital. When a sector built on borrowed money and lofty valuations stumbles, individual savers, pension holders, and companies that committed capital based on optimistic forecasts bear the losses. The dot-com experience showed how quickly speculative excess can unwind, and how long recovery can take. Whether the AI market follows that script remains uncertain, Gasparino acknowledges. His core advice, though, is personal financial discipline: investors should weigh valuations against real earnings, protect gains when they appear, and recognize that no single company’s survival is guaranteed when the cycle turns.