OpenAI: From Hero to zero
OpenAI made LLMs available to the masses. No question about it.
Before ChatGPT, AI felt like something for researchers and big labs. After ChatGPT, my parents, non-technical friends, and basically everyone started using it.
For a while, “just ask ChatGPT” became almost the same as “just Google it”.
That is a massive achievement, but now the picture looks different.
ChatGPT is no longer alone
The quality gap has closed.
Gemini got better. Claude got better. Copilot got better. Open-source models got better.
For many daily tasks, people no longer care that much which model they use. They just use the one that is already in front of them.
And this is where OpenAI starts losing ground.
No platform advantage
OpenAI has a great product, but it does not own the platform where most people spend their time.
- Google can ship Gemini directly into Android (+ iOS in the future, deal has already happened!), Chrome, Workspace, and Search.
- Microsoft can push Copilot into Windows, Office, GitHub, and enterprise workflows.
OpenAI has to fight for distribution every single day.
If AI is bundled directly into the operating system, browser, IDE, and productivity apps, users will often pick convenience over model preference.
That is not a model-quality problem, it is a platform problem.
The business model problem
There is another issue: economics.
Companies like Google, Microsoft, and Apple can fund AI from multiple profitable businesses. They can accept thinner margins on AI because they earn money elsewhere.
OpenAI is in a tougher position. Training and serving frontier models is expensive, competition is brutal, and the company depends heavily on external capital.
That is a hard setup when rivals can subsidize AI as part of a much larger ecosystem strategy.
From hero to zero?
Not really zero.
OpenAI is still one of the key reasons AI became mainstream. It still ships top-tier models and keeps pushing the field forward.
But being the innovator is not the same as being the long-term winner.
Tech history is full of companies that invented the future, but lost the distribution and business battle later.
And beyond product and distribution, there is also a trust question.
OpenAI started with a very public mission around benefiting humanity. In parallel, its positioning moved toward commercial scale, aggressive enterprise expansion, and now also defense-related partnerships. You can agree or disagree with that direction, but the shift is hard to ignore.
If users and developers start feeling that the original mission was mostly branding, that also weakens long-term loyalty.
What this means for us
As developers and knowledge workers, we should care less about brand loyalty and more about practical outcomes.
Use the model that fits your workflow, your budget, and your ecosystem.
The winner might not be the model with the best benchmark score. The winner will likely be the one that is available everywhere, cheap enough, and good enough, and trusted enough by users, developers, and companies to become part of their daily workflow.
Right now, that race is still wide open. OpenAI is losing ground though.