OpenAI has ruled out completing an initial public offering in 2026, with CEO Sam Altman saying concerns over AI safety make this an “ill-advised moment” to go public.
For enterprise customers, remaining private could give OpenAI more freedom to prioritize safety and infrastructure spending without pressure from public shareholders. However, it also delays the financial and governance disclosures that would give customers greater visibility into one of their most important AI suppliers.
Pressure has been building on AI labs to establish proper governance for their AI models, after researchers warned that continued AI progress could pose an extinction risk to humanity. At the same time, researchers have reported incidents in which OpenAI agents escaped restricted testing environments and accessed external services, including Hugging Face.
“I actually think that, given everything happening with safety, right now would be an ill-advised moment to go public, and we don’t feel pressure on that,” Altman told Fortune magazine.
OpenAI chief scientist Jakub Pachocki said last week that AI labs may need to slow development to compensate for rapid research advances and increasingly unreliable monitoring. Anthropic CEO Dario Amodei published a blog post a few days later calling for a similar pacing of frontier model development.
Altman, Amodei and SpaceX CEO Elon Musk have each supported slowing some forms of advanced AI development, although they have not announced a coordinated plan. Any resulting slowdown could affect AI investment and company valuations. But if industry leaders are unable to establish a set of rules to govern the wider sector, these agreements to slow development may prove short-lived as rivals seek a competitive advantage.
OpenAI’s delay could benefit Anthropic
OpenAI’s decision could give rival Anthropic more room to pursue its reported late-2026 IPO without competing directly for investor attention. Some investors have reportedly discussed a valuation approaching $2 trillion, which would place Anthropic among the most highly valued companies ever to enter public markets. It recently moved its IPO timeline towards mid-October.
OpenAI has not cited Anthropic’s IPO plans as a reason for delaying its own. However, avoiding overlapping listings could reduce competition for investor attention. Anthropic was previously the smaller of the two, but advances in Claude Code and Claude Work have shifted its fortunes. It reportedly reached $65 billion in annualized revenue last month, almost double OpenAI’s figure, although the two companies report revenue differently.
Anthropic’s reported IPO preparations suggest that it has reached a different conclusion about whether safety concerns should delay a public listing. Anthropic has faced its own safety controversies, including concerns that its models could potentially support biological-weapons research.
It also appears to have mended its relationship with the White House, which was thrown into disarray when the Pentagon labelled it a supply chain risk. The continued use of Anthropic’s Mythos model across several U.S. departments, despite earlier efforts to remove it from federal offices, may indicate that the administration’s position has softened.
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Getting Chinese AI labs to cooperate
Any industrywide slowdown would also require cooperation from Chinese AI labs, particularly as competition between the U.S. and China intensifies. Microsoft has welcomed the idea of pacing development, while Google DeepMind CEO Demis Hassabis has previously called for a supervisory framework, but it remains unclear whether Chinese AI labs support similar restrictions.
US and Chinese officials are set to hold a series of talks on AI ahead of Xi Jinping’s planned visit to the US on Sept. 24. Chinese state media has criticised Anthropic for reportedly attempting to shape global AI rules through lobbying and warnings that some Chinese officials regard as exaggerated.
Chinese officials may remain wary that a slowdown would restrict competitors abroad while allowing U.S. companies to retain an advantage. For enterprise customers, the larger test is whether discussions about slowing AI development produce measurable safeguards, disclosure requirements and deployment controls — or remain voluntary promises that competing labs can abandon.