The Path to Profitability

The next trillion-dollar tech company won't be built by creating the best AI model—it will be built by controlling how, where, and why people use AI. Just as Microsoft didn't win the PC era by making the best chips, today's AI leaders are racing not just to build better models, but to become the indispensable platform through which AI is accessed and deployed. Last quarter, over 50% of all venture capital funding went to AI-focused companies, totaling more than $60 billion of investment. The extreme rate with which VC firms are pouring money into Artificial Intelligence begs an important question: what is the path to profitability for companies like OpenAI?

AI startups have a relatively straightforward revenue model – subscription-based pricing for access to cutting-edge models and usage-based pricing for access to the API. Extremely high R&D and capital costs make attracting more paid users a requirement, but doing this also increases their marginal costs of inference. Therefore, paid users must offset their own marginal costs while subsidizing the costs of free users before beginning to chip away at those massive fixed costs that investors are currently covering. How can these aggressive revenue numbers be achieved without the assistance of external capital?

OpenAI and the other labs creating foundation models have no competitive moat and few products that fit wide swaths of the market. They have APIs that allow developers to create products, but that further commoditizes their main strength.

The Moat of the Personal Computer Revolution

Let's look at the first transformational change in technology to see how our current future might play out. Much like our foundation models today, the integrated circuit and transistor were commodities. The moat that helped lock in decades of Windows/Intel hegemony was Microsoft's platform deals.

It wasn't the hardware itself that dictated dominance, but the strategic positioning of software as a control point—Windows became the layer through which users interacted with computing, and Intel became the default engine beneath. The real power lay not in the invention, but in the ecosystem built around it: developer tools, third-party software, enterprise integrations, and, most critically, distribution deals that ensured Windows shipped on nearly every PC.

Foundation models may be the new transistors—powerful, essential, but increasingly commoditized. The question becomes: who builds the new "Windows" for AI? Will it be a developer platform, a ubiquitous interface layer, or a vertically integrated product experience? The companies that succeed in building sticky platforms around foundation models—whether through proprietary data, user workflows, or ecosystem lock-in—may become the long-term leaders in artificial intelligence.

It's interesting to note the trend of OpenAI enhancing its API with features typically reserved for subscribers at a faster pace. They're also adding features to their API that will make it more difficult for developers to switch model providers. Look no further than how their new responses API compares to the original chat completions API. The new API is stateful, which makes it both easier to build solutions with and far more difficult to switch out with the API of another provider.

But there's another layer to this. We're seeing the early signs of this platform consolidation. Just as Microsoft leveraged pre-installation deals and developer incentives to make Windows indispensable, today's AI leaders are racing to become the default platform on which others build. Microsoft's investment in OpenAI, Anthropic's partnership with Amazon, and Google's embedding of Gemini into its product suite all mirror those earlier moves—where distribution, not just innovation, becomes the true competitive edge. The players who control not just the models, but the channels of user interaction—browsers, operating systems, productivity tools, search, or even chip infrastructure—are best positioned to own the AI era.

We're entering a phase where control over context becomes as important as control over compute. Just as Windows became the context for productivity and the web browser the context for search, whoever owns the AI context—how, where, and why users invoke intelligence—will shape the future. That's the real platform play.