Altman pushes back as OpenAI revenue questions mount

Sam Altman said OpenAI is making “well more” than $13 billion in annual revenue during a BG² podcast interview with Microsoft CEO Satya Nadella. He rejected reports of a near-term IPO plan, while framing the company’s large computing commitments as a forward bet on continued growth.

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Altman pushes back as OpenAI revenue questions mount

OpenAI CEO Sam Altman used a joint interview with Microsoft CEO Satya Nadella to push back on questions about whether OpenAI’s revenue can support its computing ambitions. The exchange centered on reported annual revenue of around $13 billion, more than $1 trillion in spending commitments for computing infrastructure over the next decade, and speculation about when the company might eventually go public.

Altman disputes the $13 billion framing

The discussion took place on the BG² podcast, where host Brad Gerstner, founder and CEO of Altimeter Capital, raised reports that OpenAI is bringing in around $13 billion in revenue. That number is sizable on its own, but Gerstner placed it against the scale of OpenAI’s reported infrastructure commitments.

Altman rejected the premise that $13 billion fully captures the company’s current revenue position. “First of all, we’re doing well more revenue than that. Second of all, Brad, if you want to sell your shares, I’ll find you a buyer,” Altman said, drawing laughter from Nadella. “I just — enough. I think there are a lot of people who would love to buy OpenAI shares.”

Gerstner quickly responded, “Including myself,” making clear that the concern about OpenAI’s economics did not mean a lack of investor interest.

Altman then turned the discussion toward the company’s critics. He said some people who express concern about OpenAI’s computing plans would still be eager to buy shares if given the chance. His broader point was that public anxiety about spending does not necessarily reflect weak demand for ownership in the company.

The computing bet behind OpenAI’s growth plan

The sharpest tension in the interview came from the gap between reported revenue and the scale of future infrastructure commitments. OpenAI has made more than $1 trillion in spending commitments for computing infrastructure for the next decade, according to the discussion described in the source article.

Altman did not deny that the company is taking risk. He acknowledged that OpenAI “might screw it up” in some ways, including by failing to secure enough computing resources. But he also said that “revenue is growing steeply,” and presented the infrastructure strategy as a forward-looking bet rather than a simple cost burden.

That bet rests on several expectations Altman named in the interview:

  • ChatGPT will keep growing.
  • OpenAI can become one of the important AI clouds.
  • The company’s consumer device business will become significant and important.
  • AI that can automate science will create huge value.

Those points show how OpenAI is positioning its spending. The company is not describing compute only as support for today’s products. Altman framed it as the foundation for multiple future businesses, including ChatGPT, AI cloud services, consumer devices, and systems aimed at automating science.

Microsoft’s role remains central

Nadella’s presence in the interview mattered because the conversation was also about the partnership between OpenAI and Microsoft. Nadella said OpenAI h as “beaten” every business plan that it has given Microsoft as an investor.

That claim was important because it directly addressed the reliability of OpenAI’s internal projections. If OpenAI has outperformed the business plans it presented to Microsoft, Nadella’s comment supports Altman’s argument that the company’s revenue trajectory should not be judged only by outside reports.

At the same time, the interview did not remove the core question facing OpenAI. The company is operating with very large infrastructure commitments, and Altman himself acknowledged that execution matters. The issue is not simply whether revenue exists today, but whether growth continues strongly enough to justify the company’s computing strategy.

IPO speculation gets a firm response

Gerstner returned later to OpenAI’s revenue and possible IPO plans. He speculated about the company reaching $100 billion in revenue in 2028 or 2029. Altman responded with a shorter, more aggressive timeline: “How about ‘27?”

That remark suggested confidence in the pace of growth, but Altman also rejected reports that OpenAI plans to go public next year. “No no no, we don’t have anything that specific,” he said.

Altman described a public listing as something he assumes may happen eventually, not as a process with a set timetable. “I’m a realist, I assume it will happen someday, but I don’t know why people write these reports. We don’t have a date in mind, we don’t have a board decision to do this or anything like that. I just assume it’s where things will eventually go.”

He also explained one reason a public company structure occasionally appeals to him. Altman said there are “not many times” when he wants OpenAI to be public, but one rare appeal would be letting critics of the company’s survival prospects short the stock. He said he would “love to see them get burned on that.”

What the exchange reveals

The interview did not produce detailed financial statements, and it did not provide a confirmed IPO date. What it did offer was a clearer view of how OpenAI’s leadership wants its business to be understood.

Altman’s message was direct: reported revenue figures are too low, revenue is rising quickly, demand for shares remains strong, and the company’s large computing commitments are tied to a broader plan for future AI businesses. Nadella added that OpenAI has exceeded the business plans it provided to Microsoft.

The remaining uncertainty is execution. Altman said OpenAI could make mistakes, especially if it does not obtain enough compute. But he also made clear that the company is choosing to spend ahead of expected demand, betting that ChatGPT growth, AI cloud ambitions, consumer devices, and science automation can support a much larger business.