Sam Altman wants OpenAI to be worth $1 trillion before it touches the public markets. That’s the number. Anything below it is, in his view, a nonstarter.
The OpenAI CEO has effectively killed any prospect of the company going public this year, calling a 2026 IPO ill-advised despite the company having already filed its S-1 registration statement with the SEC back in June. The new target is 2027, with a caveat that it could come sooner if the business environment cooperates.
A trillion-dollar threshold
OpenAI’s most recent private valuation landed at roughly $852 billion as of March 2026. That’s an extraordinary number for a company that’s still posting losses. But it’s not $1 trillion, and for Altman, that gap matters.
Internal discussions shifted over the summer. Advisers and executives began recommending a delay, pointing to volatile market conditions and the performance of other high-profile tech IPOs as reasons to pump the brakes. SpaceX’s post-IPO stock volatility, in particular, served as a cautionary example that apparently resonated with OpenAI’s leadership team.
On August 19, CFO Sarah Friar addressed employees directly, confirming that OpenAI would target a public offering in 2027. She left the door open by noting it could happen sooner if business conditions showed significant improvement, but the message was clear: 2026 is off the table.
The math behind the patience
The gap between $852 billion and $1 trillion is about $148 billion, roughly 17% growth from the last private round. For most companies, that would be a multi-year aspiration. For OpenAI, which has been roughly doubling its valuation with each fundraising cycle, closing that gap in the next several months isn’t unreasonable.
What this means for the IPO landscape
The conventional market approach OpenAI is taking, relying on traditional IPO mechanics rather than alternative listing structures, suggests the company wants a clean, straightforward public debut. No SPACs, no direct listings, no exotic financial engineering.
Friar’s messaging to employees also serves an internal purpose. Stock-based compensation is a major retention tool for AI companies competing for elite engineering talent. Giving employees clarity about a 2027 timeline, rather than letting uncertainty linger, helps manage expectations and reduces the risk of key departures driven by frustration over liquidity timelines.