OpenAI’s rise has reshaped how people think about artificial intelligence. In a little over 10 years, the company has gone from a nonprofit research organization to the creator of some of the world’s most widely used AI tools.
Before diving into OpenAI’s history, it helps to start with the latest developments. The company’s newest releases provide a snapshot of where the technology is heading.
OpenAI released GPT-5.6 on July 9, 2026, with a three-tier naming structure. Instead of a single flagship model, users can choose between Sol, Terra and Luna.
The release reflects how AI companies are organizing models around cost, which encourages easier decision-making based on user needs.
Bloomberg reported that OpenAI’s agent products reached 10 million combined users within two weeks of ChatGPT Work’s debut, nearly doubling its usage from earlier in July.
That growth curve signals a shift in how people actually use AI every day. Millions of users now hand off entire tasks to an agent and let it work with limited supervision, rather than having back-and-forth conversations with it. If this pace of adoption continues, agentic AI could become a standard part of daily work for companies of all sizes.
OpenAI’s story stretches back decades to the earliest experiments in conversational computing.
One of the earliest forerunners of AI language models was the Eliza model, developed in 1966 at the Massachusetts Institute of Technology. Eliza used a scripted pattern-matching algorithm to mimic human speech.
Despite the models’ limitations, many users treated their conversations with Eliza as genuine exchanges. Individuals seem to attribute human qualities to machines that communicate with them.
OpenAI launched on December 11, 2015, as a nonprofit organization dedicated to advancing artificial intelligence for the benefit of humanity.
Sam Altman and Elon Musk were the organization’s co-chairs at the time, with other notable names like Greg Brockman and Ilya Sutskever among its founding members. Amazon Web Services and Palantir’s Peter Thiel were some of OpenAI’s major donors.
Three years later, OpenAI introduced the first generative pre-trained transformer (GPT) in 2018. Although modest by today’s standards, GPT-1 established the foundation for every GPT model that followed.
GPT-1 combined transformer architecture with unsupervised pre-training, allowing the system to learn from massive datasets before adapting to specific tasks. Researchers began training a single model that could adapt to many different applications. That concept reshaped AI development and laid the groundwork for ChatGPT and other GPT models released since.
As OpenAI’s ambitions and orientation changed, so did its computing requirements. Its strategy switched dramatically in 2019, and that shift shaped everything that followed.
Training frontier models takes enormous computing power, which costs money that a pure nonprofit structure couldn’t raise fast enough. OpenAI addressed that gap by creating OpenAI LP, a “capped profit” company.
Investors could earn a return under the new structure, but that return was capped, with any additional value flowing back to the original nonprofit mission. The arrangement enabled OpenAI to attract better capital while preserving its founding goals.
The decision generated debate within the AI community. Some viewed it as a practical compromise, while others saw it as a departure from OpenAI’s nonprofit roots. Regardless, the move fundamentally changed the company’s trajectory.
That same year, OpenAI announced GPT-2 and made an unusual call. It withheld the full model from public release, citing concerns about misuse. Instead, the company pursued a staged release over several months. The decision sparked debate and scrutiny, mainly around safety, transparency and marketing. After all, the release approach OpenAI took did gain a lot of traction.
Some companies have answered the transparency question by publishing their models openly for anyone to inspect and run. For example, DeepSeek AI built its reputation on exactly that kind of open-source AI, and the contrast between its approach and OpenAI’s continues to shape how the industry talks about responsible release practices.
OpenAI’s biggest breakthroughs arrived after 2020, when its models reached developers, businesses, and eventually the general public.
GPT-3 represented an enormous leap in scale. With its 175 billion parameters, it quickly became one of the most discussed AI systems in the world. Developers could integrate GPT-3 into their products without training their own models, which supported startups and applications.
The company’s staged release philosophy also carried over from GPT-2, balancing accessibility with safety considerations. GPT-3 transformed OpenAI into a platform company by allowing developers to build directly on top of its technology.
OpenAI launched ChatGPT on November 30, 2022, and changed how people saw artificial intelligence almost overnight. Unlike earlier AI products, ChatGPT required little technical knowledge. Anyone with an internet connection could interact with a capable conversational system within seconds.
This ease of use led to widespread adoption. ChatGPT became one of the fastest-growing consumer applications, introducing millions of people to generative AI for the first time. According to a Reuters report, ChatGPT exceeded 1 billion monthly active users as of June 2026. For many people, ChatGPT was how AI moved from research labs and into everyday life.
GPT-4 significantly expanded OpenAI’s performance by improving reasoning and introducing multimodal inputs, enabling users to provide images alongside text.
The model also performed well on standardized tests. OpenAI reported that GPT-4 scored above the 90th percentile on a simulated Uniform Bar Examination, highlighting how quickly large language models have advanced.
Before GPT-5.6 introduced the Sol, Terra and Luna tiers, OpenAI made another change to its model strategy in 2025. OpenAI released GPT-5 on August 7 of that year as a unified system that combined lessons from its earlier models. Instead of asking users to manually select between separate models for speed or reasoning, GPT-5 handled those decisions automatically.
This system changed how users interacted with AI. Previous generations often required choosing the right model before starting a conversation. GPT-5 reduced that friction by treating intelligence as a service that adapts dynamically to the task at hand.
OpenAI’s history offers a clear view of how quickly AI continues to evolve. Each release has expanded what users expect from these systems. With GPT-5.6 now in the market and future models on the horizon, the next chapter in OpenAI’s timeline is likely closer than it seems.
