Silicon Valley AI startups reportedly raised a record $150 billion this year.
As the Financial Times (FT) points out reported On Sunday (Dec. 28), it was part of an effort by these companies to protect themselves in case the artificial intelligence (AI) investment boom peters out next year.
The report, citing Pitchbook data, shows that this year’s funding levels surpassed the previous record of $92 billion set in 2021, with companies like OpenAI And Anthropic attracting strong interest from investors.
Venture capitalists and industry experts told the FT the funding would fuel growth while providing companies with a safety cushion in the event of an investment slowdown caused by concerns over large spending on AI infrastructure.
“You should make hay while the sun shines,” said Lucas Swisherpartner of Coatue who invested in OpenAI, Data bricks And EspaceX. “2026 could bring something unexpected…when the market offers the option, build a fortress balance sheet.”
Funding levels for 2025 have been strong thanks to some record funding rounds, the FT said: 41 billion dollars for OpenAI, 13 billion dollars for Anthropic and Meta A $14 billion bet about getting started with data labeling Evolving AI.
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The report adds that cost pressures have led to more frequent funding rounds, particularly for companies working on “frontier” AI models that require huge amounts of computing power and expensive chips.
OpenAI’s revenue for this year is around $13 billion, sources close to the company told the FT. However, the startup loses billions of dollars every year as it expands its models, products, and infrastructure.
In other AI news, PYMNTS spoke Monday with Adam Hiattvice president of anti-fraud strategy at the payment orchestration platform Quicklyon the role of technology in prevent fraud.
Although AI has rightly attracted much attention for the role it has played in democratizing fraud, the report says, fraudsters do not have a monopoly on artificial intelligence.
However, the advent of AI and its applications in popular and increasingly industrialized fields fraud schemes have compressed timelines and raised the level of abstraction at which humans must operate, this report adds.
“Distinguishing between good and bad is becoming something that even a good manual assessment is not able to do,” Hiatt said. “Before, you could blame people for the problem, but that’s getting harder and harder.”