The emergence of artificial intelligence, particularly generative AI tools like ChatGPT, has fundamentally reshaped the venture capital landscape, leading to a significant re-evaluation and decline in valuations for numerous startups that predated this technological shift. More than 220 companies that once achieved billion-dollar valuations are now classified as "fallen unicorns," a list that includes prominent names such as Glossier, Savage X Fenty, AG1, and The Farmer's Dog, according to PitchBook, which provided this exclusive data to CNBC. This phenomenon is largely attributed to the AI boom, which has channeled over $250 billion into leading AI firms like OpenAI and Anthropic, thereby altering valuation benchmarks across various startup categories.
The period preceding the AI revolution was characterized by a surge in venture capital investments into American startups, spanning diverse sectors from lingerie subscriptions to scheduling software. Many of these companies were granted billion-dollar valuations even before achieving profitability, a trend fueled by readily available capital and heightened demand during the pandemic. Despite the Federal Reserve's initiation of interest rate hikes in 2022, which aimed to temper market exuberance, many founders maintained the belief that their companies could eventually grow into their elevated valuations, investors told CNBC.
However, the introduction of ChatGPT in 2022 marked a pivotal "ChatGPT moment," as described by Samir Kaul, a partner at Khosla Ventures and an early investor in OpenAI. Kaul noted that this development prompted a realization among industry observers that "the next generation of entrepreneurs, their coding language is spoken English." He further emphasized the dramatic increase in efficiency, stating that "Now you're seeing 50 engineers do what it would've taken 500 engineers to do five years ago." This profound shift necessitated a complete re-evaluation of how venture firms assessed company worth.
While publicly traded software giants such as Salesforce, ServiceNow, and Workday have experienced stock market pressures due to the perceived threat from artificial intelligence, a more subtle yet equally impactful recalibration has been unfolding within the private markets. The massive influx of over $250 billion into OpenAI and Anthropic, ahead of their expected mega-IPOs, has effectively isolated hundreds of startups founded before ChatGPT's 2022 debut. These companies find themselves in a precarious position, cut off from venture funding due to their inflated pre-AI valuations and often relying on outdated technology, yet lacking the profitability required for public market entry.
According to PitchBook data, there are 857 U.S. startups currently valued at $1 billion or more, the established benchmark for "unicorn" status. However, nearly half of these companies have not secured new funding in the past three years, rendering their existing valuations outdated, according to the private markets data firm. PitchBook's own valuation estimates indicate a significant depreciation: startups that last raised capital in 2021 are now, on average, worth 68% less, while those that last raised in 2022 have seen their valuations decline by 52%. Consequently, more than 220 companies that achieved billion-dollar valuations during the venture boom are now classified as "fallen unicorns," according to PitchBook, which provided a list of the companies exclusively to CNBC. These valuation estimates are derived from various factors, including headcount growth and comparisons with public company performance.
Immad Akhund, CEO of Mercury, a company that provides banking services to a third of early-stage U.S. venture-backed firms and recently raised $200 million in funding, told CNBC that "A lot of those companies are pre-AI, not just in their cost structure, but also in their products." He acknowledged their difficult situation, stating, "They're definitely in a difficult spot." Akhund highlighted that with "All the attention's on AI, so if you're not an AI-first company, you need really strong numbers to raise."
The roster of fallen unicorns includes a diverse array of well-known consumer brands and technology firms. Among them are Glossier, The Farmer's Dog, Rothy's, Brooklinen, and Savage X Fenty, the lingerie enterprise founded by Rihanna. These companies represent a wave of direct-to-consumer businesses that were built on the premise that digital retail could achieve software-like profit margins. Also on the list are popular podcast advertisers like the supplement manufacturer AG1 and the robo-advisor pioneer Betterment, alongside the online ticket marketplace SeatGeek. These entities thrived in an environment that rewarded aggressive growth with high valuations, based on two core assumptions: persistently low interest rates and the consistent potential for acquisition driven by engineering talent.
The AI-Driven Software Shift
The emergence of generative AI has fundamentally reshaped the venture landscape, diverting capital towards AI-native enterprises and making it exceedingly difficult for many older startups to justify their previous valuations. Enterprise software companies, particularly scheduling startups like Calendly, have been among the hardest hit, constituting the largest single category of fallen unicorns. PitchBook's list identifies 75 software-as-a-service (SaaS) firms, a number double that of fintech companies, the next largest group. This disparity underscores both the inflated valuations commanded by software startups during the 2021 venture boom and the extent to which generative AI has destabilized the foundational assumptions of the sector.
David Zhu, formerly head of engineering at DoorDash, observed a "seismic shift on the horizon" across the entire software ecosystem following the "ChatGPT moment." He examined everything from nascent startups to medium-sized firms supported by private credit and even the largest public SaaS companies. Zhu conveyed to CNBC his central thesis: "all workflow-driven enterprise SaaS companies will be either disrupted or dead in the next decade." The traditional SaaS model, which integrates companies into employee workflows and often charges on a per-user basis, is particularly vulnerable to the rise of autonomous agents. After his tenure at DoorDash, where he managed over 200 engineers, Zhu founded Reevo, an AI platform designed to automate corporate sales and marketing functions.
Zhu contends that companies developed before generative AI are burdened by inefficient staffing models and software architectures designed for a pre-AI world, making their transformation challenging. He asserted that "Unless they make a stark, 180-degree pivot to rebuild the exact same thing from scratch, they're going to slowly fail." This situation implies that "investors would rather just bet on new entrepreneurs at lower valuations rather than double down on older startups."
Many of the companies identified by CNBC either did not respond to inquiries or declined to comment. Skydio, a drone manufacturer whose valuation PitchBook estimated to have fallen from $2.5 billion to $509 million, issued a statement refuting this "third-party speculation" as "false and not based on Skydio's operations or the exponential growth we are seeing in revenue and customers." Weeks later, Skydio announced a $110 million funding round from existing investors, which reportedly raised its valuation to $4.4 billion. An AG1 spokesperson did not provide a statement for the article, but following CNBC's inquiry, Reuters reported that the supplement maker was exploring a sale of part or all of the company at a $2 billion valuation, a figure that would include its debt.
Investors and founders suggest that companies that have not secured funding since 2021 or 2022 are unlikely to do so again. Without access to venture capital or a viable path to an initial public offering, the most probable outcome for many fallen unicorns is an acquisition at a significantly reduced valuation. Andrew Akers, an analyst at PitchBook, noted that a company's failure to raise funding is typically "a red flag," often indicating stagnant or negative growth. While some startups might forgo fundraising due to robust profitability, Akers clarified that this is an exception rather than the rule, adding, "Underneath the surface, I think there are a lot of dominoes to fall."
Evidence of this market reset has emerged this year. In February, Stash, an investment and savings application, was acquired by Singapore-based Grab for an enterprise value of $425 million, which was below the approximately $660 million invested into the company over its lifetime. In the same month, another fintech firm, Step, was acquired by YouTube star MrBeast for an undisclosed amount, leading investors to speculate that the purchase price was far below the approximate $500 million the startup raised before the deal. Ryan Falvey of Restive Ventures, which invests in fintech firms, noted that valuations have compressed by about sixfold from the 2021 peak of 50 times future revenues, meaning a company with the same revenue is worth about 85% less in today's market than five years ago, Falvey told CNBC.
Before this market reset, a startup could often be sold to a larger technology company looking to acquire the smaller firm's engineers for roughly $2 million per coder, according to Khosla Ventures' Kaul. A firm with 100 engineers would be worth at least $200 million to $300 million, he said. However, that assumption, which provided a floor under startup valuations during the boom, evaporated after AI coding tools allowed far smaller teams to build products, leaving exit opportunities few and far between.
According to Falvey, post-GPT startups are now outperforming their older competitors. He described investments made over the past three years as "undoubtedly the best" his firm has made, observing that by 2023, companies invested in post-ChatGPT were already generating more revenue than most pre-ChatGPT investments. Generative AI may ultimately reduce the amount of capital required to build successful software companies, challenging a core assumption that fueled the venture boom of the past decade. The shakeout is likely just beginning, with AI's impact reverberating across the business funding ecosystem. Older software firms, Kaul said, still rely on business models built around charging customers based on the number of employees using their products, an approach he believes AI will undermine as companies automate more white-collar work. Software providers will need to shift toward outcome-based pricing models and AI-native infrastructure to survive, he said. Kaul frequently challenges presenters with the question, "why can't OpenAI, Anthropic or Google do this?" For most, he noted, the answer is, "They can."
