AI significantly lowers startup valuations for companies that existed before ChatGPT.

      TL;DR: Over 220 former unicorns have lost their billion-dollar valuations as the AI boom shifts venture capital focus to a select few companies. According to PitchBook data, startups that last raised funds in 2021 are now worth, on average, 68% less, with SaaS firms being the most affected group.

      The AI boom has resulted in a dichotomous startup economy. Companies leveraging generative AI are securing unprecedented valuations, while those that last raised funds before the November 2022 launch of ChatGPT are seeing their valuations plummet. PitchBook estimates indicate that more than 220 companies, including consumer brands like Glossier, Savage X Fenty, AG1, and The Farmer’s Dog, have fallen below the billion-dollar mark.

      The statistics are striking. Startups that last raised in 2021 have an average value that's 68% lower, while those that last raised in 2022 have experienced a 52% drop. The biggest decline is observed in enterprise software, where 75 SaaS companies are listed as fallen unicorns on PitchBook, double the number of fintech firms, the second-largest category. Notable names include scheduling company Calendly.

      Where the funding went: The capital hasn't vanished but rather shifted. In the first quarter of 2026 alone, AI startups raised $255.5 billion globally, exceeding the total AI venture funding for the entirety of 2025. However, this funding was highly concentrated, with three deals—OpenAI's $122 billion round, Anthropic's $30.6 billion raise, and xAI's acquisition by SpaceX—accounting for 67% of all capital raised. Venture firms that invested in these early successes are experiencing returns that validate larger bets on AI.

      The concentrate of funding affects all levels of the investment ecosystem. Of the 1,546 AI deals logged in Q1 2026, the vast majority of capital flowed to a select few companies. Sovereign wealth funds from Singapore, Saudi Arabia, and Abu Dhabi have become crucial players in frontier AI funding, further skewing capital allocation toward a small number of firms operating at the infrastructure level.

      For startups that raised funds before ChatGPT, this concentration poses a significant threat. Venture investors who might have supported a SaaS company experiencing 40% growth are now rechanneling that funding into AI-native firms growing at 200%. In early 2026, AI-native enterprise spending soared 94% year-on-year, while traditional SaaS growth rates declined to single digits, except for the strongest players.

      The SaaS reckoning: Enterprise software companies have suffered the most due to a structural shift. The introduction of generative AI and intuitive coding platforms allows non-developers to create customized applications using natural language prompts, directly undermining the value of conventional SaaS products that charge $50 to $200 per user per month.

      The market has adjusted accordingly. Earlier this year, software stocks briefly traded at a forward price-to-earnings discount compared to the S&P 500, a phenomenon that had never occurred previously. For private SaaS companies still holding on to valuations from 2021, the gap between their last recorded price and the actual market price has become insurmountable.

      This issue is self-reinforcing. These companies face challenges in raising new rounds without accepting drastic down rounds that would dilute early investors and employees. They cannot go public, as the IPO market requires a credible AI narrative, which most pre-ChatGPT SaaS companies lack. Additionally, many are not profitable enough to sustain operations long-term without outside funding.

      The acquisition route: Lacking access to venture capital or a feasible public offering, many fallen unicorns may only find opportunities through acquisitions at a fraction of their previous values. AI-native companies like Cognition are commanding valuations of $26 billion while producing products predominantly powered by their own AI, setting a benchmark that pre-ChatGPT startups struggle to match in both technology and capital efficiency.

      Some companies may endure by pivoting swiftly to AI. Those able to redesign their core products around AI-native frameworks, shift from seat-based pricing to usage-based or outcome-based models, and leverage their existing customer base to enhance distribution for AI features may find a way forward. However, such a pivot necessitates both engineering talent and financial runway, both of which are dwindling for firms burdened by outdated valuations.

      The scale of the situation is historically atypical. Previous venture cycles did give rise to overvalued startups, as seen in the dot-com bust, the 2015 unicorn correction, and the 2022 rate shock, but none coincided with a technological disruption that rendered the primary business model of an entire category of startups obsolete. The winners in the AI landscape are attaining returns that seemed unimaginable three years ago, while the losers are realizing that a billion-dollar valuation from 2021 is not a standard; it is a relic of a market that no longer exists.