AI & Machine Learning
Business Insiderabout 2 hours ago
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Mercor's CEO says it now spends more on AI tokens than employee salaries

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Mercor's CEO says the $10 billion startup now spends more on AI tokens than employee salaries, predicting a broader shift where AI compute costs surpass labor costs for enterprises.

Mercor's CEO says it now spends more on AI tokens than employee salaries

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The Big Picture
Brendan Foody, CEO of the $10 billion AI startup Mercor, revealed on the '20VC' podcast that the company now spends more on AI tokens for internal agents than on employee salaries. Mercor, which helps companies like OpenAI and Anthropic train AI models, uses AI agents across project management, recruiting, accounting, and fraud detection, and has conducted over 5 million AI-assisted interviews. Foody predicts that within five years, the average enterprise will spend more on compute than headcount, driven by falling AI costs and improved capabilities—a Jevons paradox effect. This comes amid debate over whether rising AI spending yields returns, with Uber's COO questioning the link. Foody believes humans will still be needed for tasks AI cannot do, but inference costs will eventually exceed labor costs.
Why It Matters
Mercor's spending shift signals a future where AI compute costs rival or surpass human salaries, forcing companies to rethink labor economics and ROI on AI. If this trend scales, it could redefine corporate budgets, job roles, and the value of human vs. machine work, especially as AI agents take on more complex tasks.

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Brendan Foody at the 2025 Breakthrough Prize Ceremony at Barker Hangar on April 05, 2025, in Santa Monica, California.
Brendan Foody at the 2025 Breakthrough Prize Ceremony at Barker Hangar on April 05, 2025, in Santa Monica, California.
Brendan Foody is the CEO of Mercor.

Taylor Hill/FilmMagic via Getty Images

  • Mercor's CEO says the $10 billion startup now spends more on AI tokens than employee pay.
  • Before long, he says, the average company could be spending more on AI compute than on salaries.
  • Some tech leaders are questioning whether soaring AI costs are producing returns.

What happens when a company spends more on AI than on its workers? Mercor's CEO says his startup is already finding out.

"Right now we're spending more on tokens for our internal agents than we are on employee head count," Foody said during an appearance on the "20VC" podcast on Monday.

When host Harry Stebbings asked if Mercor's token spending on AI agents exceeded salaries, Foody replied: "That's correct. It's pretty incredible."

Mercor — a $10 billion startup that helps companies such as OpenAI and Anthropic train AI models through a network of its human experts — has become one of the fastest-growing companies in the AI ecosystem since its 2023 launch.

As of October 2025, per PitchBook, it had around 300 employees. The company did not respond to a request for comment.

Foody said Mercor uses AI agents across a wide range of functions, including project management, recruiting, accounting, fraud detection, and candidate evaluation. The company has conducted more than 5 million AI-assisted interviews, he said.

The executive believes Mercor's spending patterns foreshadow a broader shift across corporate America.

"I would bet that in five years the average enterprise spends more on compute than headcount," Foody said.

When AI costs more than employees

Foody's comments come amid a broader debate among executives over whether rising AI spending is translating into meaningful business returns.

Uber COO Andrew Macdonald recently said he has yet to see a clear link between rising AI spending and proportional productivity gains.

Foody said that falling costs and rapidly improving model capabilities are driving a Jevons paradox-style effect, where cheaper AI leads to significantly more consumption rather than less.

He said Mercor measures the performance of different AI models for specific business tasks and evaluates whether newer models offer better value.

The result, he said, is a future in which AI becomes a core operating expense for companies, potentially rivaling or surpassing the cost of human labor itself.

"Humans will still play an important role at the things models can't do," he said. "But I expect that cost of inference, cost of compute will exceed that."

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