It’s difficult to ignore how far this company has come since its founding. Greg Brockman was hosting early meetings in his living room in December 2015. By 2021, the organization had only raised $133 million out of $1 billion in pledges. By the standards of what was being envisioned within, the original Pioneer Building headquarters in San Francisco’s Mission District was modest.

Amazon, NVIDIA, SoftBank, Microsoft, Sequoia Capital, BlackRock, Fidelity, and Temasek are among the names supporting OpenAI that now resemble a guest list for an international financial summit. There is a feeling that something more significant than typical market enthusiasm is at play when so many serious institutions invest this much money.

The speed is what makes the OpenAI valuation truly intriguing and challenging to evaluate. The quickest technology platform to reach 10 million users, followed by 100 million, OpenAI is currently aiming for 1 billion weekly active users. Here, revenue that typically took years to develop came in quickly: $1 billion within a year of ChatGPT’s launch, $1 billion every quarter by the end of 2024, and currently $2 billion every month. According to the company, its revenue growth is four times faster than that of Alphabet and Meta during their pivotal years. You don’t say that in a low voice. Additionally, investors appear to accept it.

Nevertheless, a data center can overcome the disparity between revenue growth and profitability. OpenAI anticipates an operating loss of about $8 billion in 2025, and expenditures are predicted to rise sharply to $17 billion in 2026, $35 billion in 2027, and $45 billion in 2028. Large language model training and operation come at a truly astounding computational cost. As you watch this happen, the question of when the cost curve bends naturally arises.

According to OpenAI, the flywheel logic is true: better compute leads to better models, better models lead to better products, better products lead to adoption, adoption leads to revenue, and revenue finances more compute. The narrative is tidy. It’s another matter entirely if everything goes as planned.

Complicating matters further is the corporate structure. What started out as a nonprofit was converted to a capped-for-profit in 2019. In October 2025, it underwent yet another restructuring to become a Delaware-based public benefit corporation, with Microsoft holding 27% of the PBC, employees and other investors holding the remaining 47%, and the OpenAI Foundation holding 26%.

Opponents, such as former workers who signed a legal letter titled “Not For Private Gain,” contended that the reorganization removes significant accountability from the goal of guaranteeing that AGI benefits humanity in general. When profit incentives increase this much and so quickly, it’s still unclear if a PBC structure offers enough safeguards.

The business case seems to have the strongest foundation on the enterprise side. Over 40% of OpenAI’s revenue currently comes from enterprise use, and by the end of 2026, the company hopes to achieve consumer parity. Over 15 billion tokens are processed by APIs every minute. The coding agent Codex now has over 2 million weekly users, a fivefold increase in just three months.

Vanity metrics are not what these are. Companies don’t continue to renew contracts on that scale unless their workflows are functioning properly. The most recent model, GPT-5.4, seems to be promoting genuine engagement throughout agentic, or mostly autonomous, business processes.

On its own terms, the infrastructure strategy merits consideration. OpenAI is no longer reliant on a small number of cloud service providers. With silicon from NVIDIA, AMD, AWS Trainium, Cerebras, and a custom chip developed in collaboration with Broadcom, the compute portfolio currently includes Microsoft Azure, Oracle, AWS, CoreWeave, and Google Cloud on the cloud side.

Although training fleets continue to rely mostly on NVIDIA’s GPUs, the intentional diversification shows that OpenAI views compute as strategic infrastructure rather than a vendor relationship.

It makes sense to draw comparisons to past technological turning points, such as electricity, the highway system, and the internet. This argument is made explicitly by OpenAI, which frames the capital coming into the company as something akin to nation-building capital for an intelligence layer that will eventually power the entire economy.

Maybe the framing is right. It’s also possible that it’s the kind of story that seems most plausible just when it needs to be examined the most. From the inside, it can be difficult to distinguish between real infrastructure and an extremely costly wager.

The OpenAI valuation appears to have reset expectations regarding the potential value of private technology companies prior to going public. The most recent round raised over $3 billion by reaching individual investors through bank channels for the first time, and ARK Invest is incorporating OpenAI into a number of its ETFs.

Ownership is growing. If it comes to pass, the benefit is becoming more widely available. That’s a significant change from how these things typically operate, and it might be the most subtly important detail buried in a huge announcement.

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