‘Technology unicorns’ are no longer rare

In The Social Network (2010), The film tells the story of the formation of Facebook and the legal disputes surrounding co-founder Mark Zuckerberg, with a section related to the goals of the social network. “A million dollars isn’t great,” one person tells Zuckerberg (played by Jesse Eisenberg). “You know what’s really cool? It’s a billion-dollar valuation.”

After 16 years, Facebook changed its name to Meta and reached a value of 1,600 billion USD. At that time, a company valued at one billion USD was so rare that it was called a unicorn.

The term Unicorn, used to describe a private startup with a market capitalization of at least $1 billion, was first coined by famous venture capitalist Aileen Lee in 2013 because businesses reaching such milestones were rare and hard to find back then. But today, “seeing” unicorns is no longer something of a myth.

In fact, things are changing rapidly. According to technology and market capital research firm Pitchbook, in 2021 alone, a year before ChatGPT appeared and sparked the AI ​​wave, more than 630 unicorns were formed. As of the end of 2025, there are 1,569 active unicorns. Meanwhile, data from analysis company CB Insights shows that there are more than 1,300 AI startups valued at over 100 million USD in the first 10 months of 2025 with 498 unicorns.

According to the Global Top 100 Unicorns report published by auditing and consulting company PwC in November 2025, the total value of the top 100 unicorns reached 2,949 billion USD, up from 2,054 billion USD the previous year. These 100 unicorns all have a valuation of $8 billion or more – far exceeding the minimum $1 billion mark to become a unicorn, the top 5 names reach a valuation of more than $100 billion and 43 of these complete funding rounds in 2025.

Theo Rest of Worldthe unicorn boom shows that the original standards gradually become outdated. This site points out that the boom of unicorns began in the 2010s, when record low interest rates created huge capital flows from venture capital funds rushing into startups, caught up in the race for “growth at all costs”. The situation was pushed to a climax by the Covid-19 pandemic. Lockdown measures restricting investors’ ability to travel have caused big deals to quickly negotiate via Zoom, while technology stocks benefit from the sentiment that people will live attached to computers for the foreseeable future.

You can look at the Tiger Global fund to see the “degeneration of unicorn quality” compared to more than a decade ago. In 2021, this is the most productive venture investor in the world with the “spray-and-pray” strategy (spray money and pray) even though this approach comes with many risks. They are willing to spend money quickly, bypassing many rigorous appraisal processes to gain the right to contribute capital to potential startups.

But mistakes surfaced later. In the context of soaring interest rates and geopolitical fluctuations, the wave of “spending money” easily ended. When the pandemic subsided, startups that had relied on successive rounds of investment to survive fell into difficulty, mass layoffs, and even closures.

Some of Tiger Global’s investments have failed miserably, such as the FTX cryptocurrency platform collapsing, and founder Sam Bankman-Fried being convicted of fraud; or the Indian educational technology company Byju’s, once invested by this fund and valued at 22 billion USD, went bankrupt amid a series of lawsuits. Tiger Global also sharply reduced investment capital by 56% in 2022. In 2023, they only made 40 venture capital deals, while the year before that was 300 deals. The same year, only 133 billion-dollar startups were founded.

However, the AI ​​boom helped major investments return, although not yet at the peak of 2021. Tiger Global then invested in a number of AI companies that later became unicorns, such as Scale AI, OpenAI. “The availability of private capital, a stable macroeconomic backdrop and strong investor interest in areas such as AI or financial technology (fintech) create a solid foundation for unicorn formation,” Kat Kravtsov, PwC’s head of capital markets in the UK, said on the blog.

According to data from UBS bank, total global spending on AI is estimated to reach 375 billion USD in 2025 and is forecast to reach 500 billion USD this year. Faced with this number, some experts are optimistic, but others assess that excessive spending is forming an “AI bubble”.

“Soaring asset prices and overvaluation suggest an AI bubble is the most likely outcome,” Jared Bernstein, former chairman of the White House Council of Economic Advisers, told CNBC.

“When a bubble forms, what will be the fate of the unicorns it creates? Will anyone learn the lesson?”, Rest of World ask questions.