Inside the New AI Billionaire Boom: Who’s Cashing In, How Fast, and What Comes Next
A New Class of AI Billionaires Emerges as Start-Up Valuations Soar
A global artificial intelligence investment boom has rapidly created a new class of mostly under‑40 “paper billionaires” at start‑ups such as Scale AI, Cursor, Perplexity, Figure AI, Mercor, Safe Superintelligence, Harvey and Thinking Machines Lab, according to company statements, venture capital data and news reports compiled through late 2025. While some observers compare these founders to Gilded Age railroad barons, others warn that their fortunes depend heavily on still‑untested business models and frothy private market valuations.
Background: How the AI Boom Created Rapid Wealth
The latest wave of AI wealth followed the late‑2022 public release of OpenAI’s ChatGPT, which triggered intense global interest in so‑called generative AI systems. Venture capital investment into AI‑focused companies surged in 2023–2025, with investors racing to back infrastructure providers, model labs and application‑layer start‑ups. According to data from PitchBook and other market trackers, valuations for a subset of AI companies escalated into the tens of billions of dollars, sometimes before products reached the market.
This pattern echoes earlier technology cycles. The late‑1990s dot‑com boom transformed founders of internet infrastructure and consumer web companies into wealthy power brokers, who later reinvested in social media, cloud computing and mobile start‑ups. Historians and economists now debate whether the AI cycle will follow a similar trajectory—combining transformational technologies with speculative excess—or whether it represents a more durable shift, given AI’s potential to reshape multiple sectors, including software, finance, healthcare and manufacturing.
The current AI boom has also unfolded alongside growing public concern over data usage, copyright, labor impacts and algorithmic bias. Lawsuits such as The New York Times Co. v. OpenAI and Microsoft highlight disputes over whether AI companies’ training practices infringe on publishers’ rights. These controversies form a backdrop to debates about whether AI billionaires are capturing outsized gains from value created with publicly available data and content.
Who Are the New AI Billionaires?
Public reporting and private market data suggest that the AI boom has enriched both long‑established tech leaders and founders of newer, less familiar companies. Established billionaires such as Jensen Huang, chief executive of chipmaker Nvidia, and Sam Altman, chief executive of OpenAI, have seen their fortunes swell as demand for AI computing infrastructure and AI models has grown. Nvidia’s market capitalization surpassed US$3 trillion in 2024, according to stock exchange data, amplifying Huang’s wealth on paper. Altman, who has held equity and profit‑participation interests tied to OpenAI’s complex structure, has been widely reported as one of the most influential figures in the sector.
Alongside these high‑profile executives, a newer cohort of founders—many of them little known outside technology circles—has emerged:
- Scale AI: Co‑founded by Alexandr Wang and Lucy Guo, Scale AI specializes in data labeling and infrastructure services for AI systems. The company attracted a reported US$14.3 billion investment from Meta in June 2025, sharply boosting Wang’s estimated net worth, according to the The New York Times and PitchBook. Guo, who left Scale AI in 2018, is reported to have accumulated substantial wealth through her early stake and has since launched a venture capital firm and Passes, a platform for content creators.
- Cursor (Anysphere): Cursor, an AI‑assisted coding start‑up also known by parent company Anysphere, was founded by Michael Truell, Sualeh Asif, Aman Sanger and Arvid Lunnemark. The company reached an estimated valuation of US$27 billion in a late‑2025 funding round, according to PitchBook data cited by multiple outlets. A correction issued in December 2025 clarified that Truell and his co‑founders graduated from MIT in 2022 rather than dropping out.
- Perplexity: Perplexity, led by chief executive Aravind Srinivas, operates an AI‑driven search and answer engine. PitchBook data place its valuation at about US$20 billion after funding in 2025. In a statement cited by The New York Times, the company said Srinivas “prefers to live modestly” and is more focused on “the search for wisdom” than personal wealth.
- Figure AI: Figure AI, founded in 2022 by Brett Adcock, is developing general‑purpose humanoid robots for industrial and logistics use. The company has disclosed a valuation that implies a personal net worth of about US$19.5 billion for Adcock, according to information Figure AI provided to reporters.
- Safe Superintelligence: Safe Superintelligence Inc. (SSI), created in 2024 by former OpenAI chief scientist Ilya Sutskever and co‑founders, focuses on building artificial general intelligence (AGI) with a strong emphasis on safety. PitchBook data indicate a roughly US$32 billion valuation after the company raised about US$2 billion in 2025, despite not having released a commercial product as of late 2025.
- Harvey: San‑Francisco‑based Harvey builds AI tools for legal work, including contract analysis and research. Founded by Winston Weinberg and Gabe Pereyra, the company raised multiple funding rounds in 2025, with its valuation reportedly rising from US$3 billion in February to US$8 billion by year’s end. Weinberg has publicly downplayed the significance of his reported wealth, noting in an interview that it is “on paper.”
- Thinking Machines Lab: Thinking Machines Lab, launched in early 2025 by former OpenAI executive Mira Murati, achieved an estimated US$10 billion valuation within months, according to news reports based on venture capital sources. The company released its first product later in the year after initially securing funding without a public offering.
- Mercor: Mercor, an AI‑data and automation start‑up, was co‑founded by 22‑year‑old Brendan Foody with Adarsh Hiremath and Surya Midha. The company reached a valuation of about US$10 billion in an October 2025 funding round, according to investor disclosures and reporting, making its young founders part of the “nine‑figure” or higher wealth bracket.
These valuations, however, are based on private funding rounds rather than public market prices, and individual net worth estimates rely on assumptions about founders’ ownership stakes, liquidation preferences and potential dilution in future financing.
Visualizing the AI Start-Up Ecosystem
The AI billionaire boom is closely linked to rapid expansion in the broader AI infrastructure and start‑up ecosystem, spanning data centers, chips, model labs and application companies.
Speed of Wealth Creation: From Launch to Billionaire in Months
Many of the new AI fortunes have been created far faster than those associated with earlier generations of tech leaders. Elon Musk, for instance, became a millionaire after early ventures such as X.com and PayPal were sold to eBay in 2002, but his billionaire status emerged later, as Tesla and SpaceX grew and public markets repriced his holdings. By contrast, most of the new AI founders launched their companies after ChatGPT’s rise and saw valuations rise steeply within two to three years.
Thinking Machines Lab, announced by Mira Murati in February 2025, reportedly attained a US$10 billion valuation by June that year, even before its first product release. Safe Superintelligence, led by Ilya Sutskever, is understood to have raised US$2 billion in 2025 at a valuation of roughly US$32 billion without a commercial product on the market. Harvey’s valuation climbed from US$3 billion to US$8 billion across three funding rounds in a single year, while Cursor’s valuation leapt to US$27 billion in late 2025.
Some investors view this pace as justified by AI’s perceived potential. Others caution that it may reflect speculative dynamics reminiscent of previous asset bubbles. Jai Das, a partner at Silicon Valley venture firm Sapphire Ventures, compared AI founders to 19th‑century railroad barons but warned in comments reported by The New York Times that their wealth could be fleeting if companies fail to meet high expectations. Das posed a central question: which of these firms will endure and which founders will remain “true billionaires,” as opposed to “paper billionaires” whose wealth evaporates in a downturn.
“The question is which of these companies is going to survive,” Das said. “And which of these founders can actually end up really being true billionaires and not just paper billionaires.”
Young Founders and the Return of the “Boy Billionaire” Narrative
The demographic profile of the new AI billionaires recalls earlier tech booms in which very young founders became central figures. Larry Page and Sergey Brin co‑founded Google in their mid‑20s in 1998, while Mark Zuckerberg launched Facebook in 2004 at age 19. In the current cycle, founders like Aravind Srinivas of Perplexity and Brett Adcock of Figure AI are in their 30s, while Cursor’s Michael Truell and his co‑founders are in their 20s, having graduated from MIT in 2022.
Mercor’s founders are even younger. Chief executive Brendan Foody, 22, left Georgetown University to build the company with high‑school friends Adarsh Hiremath and Surya Midha. By late 2025, investors had valued Mercor at roughly US$10 billion, effectively placing its founders in the nine‑figure wealth bracket while they were still in their early 20s.
Margaret O’Mara, a University of Washington historian who studies the tech economy, told The New York Times that the AI era resembles the original Gilded Age—and the dot‑com period—in making “very young people very, very, very rich, very quickly.” Proponents argue that this concentration of resources in ambitious, technically skilled founders can accelerate innovation. Critics point out that it can also reinforce age and network advantages, particularly for individuals with access to elite universities, venture capital firms and major tech employers.
Gender and Representation: Mostly Men, Few Women
Despite high‑profile roles for some women in AI research and leadership, the wealth generated by the AI boom has so far flowed mainly to male founders. Among the new billionaires and near‑billionaires identified in recent reporting, only a small number—such as Scale AI co‑founder Lucy Guo and Thinking Machines Lab founder Mira Murati—are women.
Historians and sociologists say this pattern is consistent with broader trends in venture capital and start‑up formation, where women have long received a disproportionately small share of funding. O’Mara described the AI boom as amplifying the “homogeneity” of Silicon Valley’s wealth‑holding class. Diversity advocates argue that the composition of AI leadership has implications not only for who profits from the technology, but also for how systems are designed and whose needs they prioritize.
Industry groups and some large technology companies have announced initiatives to channel more capital to underrepresented founders and to broaden access to AI education. However, early data on ownership of high‑valuation AI firms suggest that gender and racial disparities remain pronounced at the top of the market.
Paper Billionaires and the Risk of a Market Correction
Much of the wealth attributed to AI founders is tied up in illiquid equity. In many cases, these shares have not been sold or listed on public markets, and their quoted value is inferred from the most recent investor term sheets. This has led analysts to describe many founders as “paper billionaires,” whose fortunes could fluctuate dramatically as sentiment shifts or as companies face competitive or regulatory challenges.
Start‑ups funded at very high valuations may confront difficult choices if growth slows. Future financing rounds at lower prices—known as “down rounds”—can sharply reduce paper net worth. The experience of the dot‑com bust, when many internet‑era fortunes vanished after 2000, looms large in investors’ minds. Some financial commentators caution that AI firms with limited revenue or unproven business models are especially exposed if capital becomes more expensive or if major customers consolidate spending on a small number of large AI providers.
Founders themselves often emphasize that their goals center on building enduring companies rather than personal enrichment. Harvey’s co‑founder Winston Weinberg, for example, told reporters that he rarely thinks about becoming rich and views the company’s rising valuation primarily as a sign of investor confidence. Perplexity has stated that Aravind Srinivas is focused on research and product development, not lifestyle changes, saying the company values “the search for wisdom” over “the search for wealth.”
Broader Economic and Social Debates
The rise of AI billionaires has become part of a wider conversation about inequality, labor and the ownership of digital infrastructure. Supporters argue that concentrated rewards provide incentives for innovation and risk‑taking in an area with substantial technical and regulatory hurdles. They note that AI systems could enhance productivity across sectors, potentially generating new jobs and services, from medical diagnostics to industrial automation.
Critics question whether the benefits of AI will be broadly shared. Labor groups and researchers have expressed concern that automation could displace certain categories of work, particularly routine knowledge and clerical tasks, while leaving ownership of the underlying systems in the hands of a small elite of investors and founders. Legal disputes over data usage and copyright, including the lawsuit filed by The New York Times against OpenAI, Microsoft and Perplexity, raise further questions about how value derived from existing content should be apportioned.
Policymakers in the United States, European Union and other regions are exploring regulatory frameworks for AI, including transparency requirements, risk assessments and potential rules for high‑impact systems. Some economists suggest that tax policy, antitrust enforcement and public investment in digital infrastructure could influence how AI‑related wealth is distributed over the coming decade.
Outlook: Enduring Titans or a Short-Lived Elite?
Whether today’s AI founders will become long‑term industrial leaders or remain emblematic of a brief speculative surge remains uncertain. The durability of their fortunes will likely depend on factors such as technical execution, competitive dynamics with large established firms, evolving regulation and the broader macroeconomic environment.
If AI companies deliver sustained improvements in productivity and develop stable revenue streams, some of the current “paper billionaires” could resemble the tech magnates who emerged from earlier waves of innovation and went on to shape subsequent generations of start‑ups. If expectations exceed what the technology can reliably deliver in the near term, valuations could reset, altering the distribution of wealth across the sector.
For now, the new AI billionaire class serves as a visible marker of how quickly capital has concentrated around generative AI and large‑scale computing—and as a focal point for broader debates about who benefits from technological change.
