AI Boom Leaves Nearly Half of U.S. Unicorn Startups Without Fresh Funding as Valuations Crater

The artificial intelligence wave that has minted new fortunes for companies like OpenAI and Anthropic is simultaneously hollowing out an earlier generation of venture-backed startups, with new data showing that nearly half of America's unicorn companies have gone three years without raising fresh capital.

PitchBook, which tracks private market activity, identified 857 U.S. startups currently valued at $1 billion or more. Of that group, close to half have not raised new funding in the past three years, leaving their valuations effectively stale, according to the firm's data.

The valuation erosion has been severe. Startups that last raised money in 2021 are now worth 68% less on average, while those that last raised in 2022 have seen a 52% decline, according to PitchBook's own estimates, which factor in metrics including headcount growth and comparisons with publicly traded peers.

More than 220 companies that once crossed the billion-dollar threshold are now classified as "fallen unicorns." The list, provided exclusively by PitchBook, includes well-known consumer brands — Glossier, The Farmer's Dog, Rothy's, Brooklinen, and Savage X Fenty, the lingerie company founded by musician Rihanna — as well as podcast-advertising mainstays such as supplement maker AG1, robo-advisor pioneer Betterment, and online ticket marketplace SeatGeek.

The hardest-hit segment is enterprise software. PitchBook identified 75 software-as-a-service firms among the fallen unicorns, double the number of fintech companies, which represent the next-largest category. Scheduling startup Calendly is among the SaaS names on the list.

Investors and founders point to a single inflection point: the public release of ChatGPT in late 2022.

"The ChatGPT moment was when people said, 'Holy smokes, the next generation of entrepreneurs, their coding language is spoken English,'" said Samir Kaul, a partner at venture firm Khosla Ventures and an early backer of OpenAI. "Now you're seeing 50 engineers do what it would've taken 500 engineers to do five years ago," Kaul said. "We had to completely reshuffle how we valued these companies."

The backdrop to that reset was a venture boom fueled by cheap money and pandemic-driven demand, conditions that allowed startups to command elevated valuations before turning a profit. Many founders assumed they could grow into those numbers even as the Federal Reserve began raising interest rates in 2022, investors told reporters. Generative AI made that bet untenable.

The AI boom has funneled more than $250 billion into OpenAI and Anthropic ahead of their expected initial public offerings, draining attention and capital from older startups that are neither AI-native nor profitable enough to access public markets.

Mercury CEO Immad Akhund, whose company provides banking services to roughly a third of early-stage U.S. venture-backed firms, described the bind those companies now face. "They're definitely in a difficult spot," Akhund told reporters. "All the attention's on AI, so if you're not an AI-first company, you need really strong numbers to raise."

David Zhu, who previously served as head of engineering at DoorDash overseeing more than 200 engineers, said the structural threat to legacy software companies is existential. "The thesis I had was that all workflow-driven enterprise SaaS companies will be either disrupted or dead in the next decade," Zhu said. After leaving DoorDash, Zhu founded Reevo, an AI platform designed to automate corporate sales and marketing functions.

Zhu argued that companies built before generative AI are burdened by bloated staffing models and products designed for a pre-AI world. "Unless they make a stark, 180-degree pivot to rebuild the exact same thing from scratch, they're going to slowly fail," he said.

The SaaS model — which embeds software into employee workflows and typically charges on a per-user basis — faces particular pressure from the rise of autonomous AI agents, which can perform those workflows without human operators.

With venture capital increasingly concentrated around AI-native firms, the window for older startups to raise bridge rounds or find acquirers at their peak valuations continues to narrow, signaling a prolonged restructuring of the private tech market that is unlikely to resolve quickly.

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