It’s hard to talk about companies achieving massive growth without including the story of OpenAI.
There is no other consumer application in history that experienced the level of growth that OpenAI did. To the tune of one-million users in it’s first five days and skyrocketing to 100 million users in the first two months. For context, thats the equivalent of the one-third of the U.S. population actively using the product within a sixty day timeframe.
OpenAI’s insane growth is tied to the AI hype curve. But, the decisions they made along the way are truly distinct and it is those differentiating factors that we can attribute their growth to in the end.
OpenAI’s founding
If you don’t know the story of OpenAI’s founding, its an important tale to understand.
The company was founded in December of 2015 by a group of high-profile, experienced founders. They founding group included Sam Altman, Elon Musk, Greg Brockman, formerly of Stripe, as President/CTO, Ilya Sutskever as Chief Scientist, others from the “PayPal mafia” like Reid Hoffman and Peter Thiel.
Originally established as a non-profit, later we will look at how that contributed to its growth, the company’s goal was to explore the potential for AGI, or Artificial General Intelligence, which focuses on AI that can perform human tasks.
OpenAI’s funding
When the company was formed, initial fundraising pledges reached as high as $1 billion. However, by 2019 the company had only taken in $130 million in investor capital.
According to Tracxn, OpenAI has gone on to raise substantial amounts of capital. Which played a role in their growth.
Dec 2015 - 1B in grants
2016 - $120K seed round
2019 - $1B
Jan. 2023 - $10B
Apr. 2023 - $300M
Jan. 2024 - $5M
Apr. 2024 - undisclosed
Oct. 2024 - $6.6B
Oct. 2024 - $4B debt
Nov. 2024 - undisclosed
Mar. 2025 - $40B
That’s almost $57B in fundraising. That amount of capital will start to make sense in the next section, where we talk about the decisions they made that and why those decisions ultimately allowed them to grow at such a high rate.
growth factors
A lot has been said about the company’s decision to start out as a non-profit. What I can tell you is that, at least in the company’s early days, that decision contributed in a large part to their ability to grow so quickly.
Often a non-profit status is seen as a benefit because of the favorable tax status that comes with the designation. What gets overlooked is that for-profit entities come with a lot of burden to produce financial results. Even privately-held for-profit entities.
In the case of OpenAI, starting out as a non-profit allowed the company to make certain financial decisions, and not make others, that contributed to their rapid growth rate.
Specifically the ability to put large sums of capital to work in two places - product R&D and the hiring of elite talent. Which points us back to the vast amounts of capital the company raised.
Still, non-profit status had its limitations. So, in 2019 the company moved to a “capped profit” model.
Think of a capped profit model as a hybrid between a non-profit and a for-profit entity. The capped profit term meant that OpenAI’s investors could earn a return on their investment, but it was capped a a certain amount. For example, a 10x return on investment.
This move further enabled the company to attract investment dollars and continue their aggressive talent hiring spree and was accomplished by creating a subsidiary, OpenAI LP, in 2019. If we look back at the funding rounds, that is when large amounts of additional capital began to flow into the company.
On top of a unique legal structure, OpenAI leveraged two other strategic decisions, enabled by large amounts of capital and top talent, to boost their growth.
The first was centered around a high-pace rate of R&D which lead to consist product releases.
In 2016, the company began the release of two products into the market that would help establish themselves as the thought-leader in the AGI space. Both Open AI Gym and OpenAI Baselines were toolkits created to establish frameworks for training AI algorithms.
The second decision came in the form of high-profile strategic partnerships. In 2016, Nvidia, the top chip maker in the world, gifted OpenAI a supercomputer called DGX-1. The company now had the hardware to perform cutting edge R&D, but it still lacked the infrastructure. To avoid the cost and timing required to establish it’s own infrastructure, OpenAI formed a strategic partnership with Microsoft in 2019. That partnership came with a $1 billion investment that expanded to $13 billion over time, and in exchange Microsoft got 49% of OpenAI Global, LLC’s equity, with profits capped at 10x of their investment. This move gave them access to Microsoft’s Azure cloud on which Open AI currently spends $10B per year.
There was one more partnership in the mix, that came once a new, more AI-friendly administration was in the White House. As part of the Stargate Project, alongside SoftBank, Oracle, and MGX, OpenAI announced a $500 billion investment into infrastructure in the U.S.
tldr
In summary, there are few key decisions that can be attributed to OpenAI’s growth.
- The election to start as a non-profit allowed the company to avoid early “red tape” and focus on becoming a thought-leader in their space.
- Leveraging capital to attract top talent, although more recently many of the original team members have left the company, created a further moat. Up until recently OpenAI’s models always outperformed others.
- The signing of key strategic partnerships gave the company access to key infrastructure that is necessary in the AI race.
There is one more piece I didn’t mention earlier. That’s the company’s pace of innovation and releasing of new products. Virtually every year since its inception the company has released a new product. Including multi-modal support in 2023 and text-to-video support through its Sora product, followed by its assistant-style product, Operator more recently.
Not only has the company remained a thought-leader, but their product team is best in class and has demonstrated an ability to execute and iterate rapidly on new products.
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