Foundational AI models will commoditize into a utility layer where companies buy "intelligence on the fly." The real, sustainable profit will be captured by application companies that leverage various models to solve specific business problems, as most enterprises lack the expertise to use raw models effectively.

Initial AI market skepticism was based on a SaaS model of selling limited-value subscriptions ('seats'). The new reality is a utility model based on consumption ('tokens'). In an agentic era, a single user can drive thousands of dollars in token usage, creating a virtually uncapped revenue stream that justifies massive infrastructure investment.

Airbnb's CEO argues that access to powerful AI models will be commoditized, much like electricity. Frontier models are available via API, and slightly older open-source versions are nearly as good for most consumer use cases. The long-term competitive advantage lies in the application, not the underlying model.

Creating frontier AI models is incredibly expensive, yet their value depreciates rapidly as they are quickly copied or replicated by lower-cost open-source alternatives. This forces model providers to evolve into more defensible application companies to survive.

The business model of selling AI access via tokens is just the start. The truly immense value creation will occur when labs turn their AGI inward to solve humanity's biggest scientific challenges, like longevity, clean energy, and materials science, capturing the resulting value.

The assumption that startups can build on frontier model APIs is temporary. Emad Mostaque predicts that once models are sufficiently capable, labs like OpenAI will cease API access and use their superior internal models to outcompete businesses in every sector, fulfilling their AGI mission.

A true platform enables its users to generate more revenue than the platform itself captures. AI companies like Anthropic are currently failing this test, as their revenue from token sales far exceeds the revenue generated by the startups building on them, creating an unsustainable circular economy.

If AI makes intelligence cheap and universally available, its economic value may collapse. This theory suggests that selling raw AI models could become a low-margin, utility-like business. Profitability will depend on building moats through specialized applications or regulatory capture, not on selling base intelligence.

Much like 'big data' evolved from a competitive advantage into a widely available commodity, AI models will likely follow the same path. So many sources will offer powerful models that they will cease to be a unique differentiator or a durable moat for businesses.