As AI infrastructure giants become government-backed utilities, their investment appeal diminishes like banks after 2008. The next wave of value creation will come from stagnant, existing businesses that adopt AI to unlock new margins, leveraging their established brands and distribution channels rather than building new rails from scratch.

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.

Historical tech cycles like the cloud and mobile demonstrate a consistent pattern: the application layer ultimately generates 5 to 10 times the value of the underlying infrastructure capital expenditure. With trillions being invested in AI infrastructure, future value creation at the application layer will be astronomically larger.

The AI value stack has evolved from chips (NVIDIA) to models (OpenAI). The next critical phase is the application layer. It's unclear if value will be captured by new application companies or if the underlying model providers will absorb all the profits, a key question for investors and founders.

As large AI models absorb functions of traditional SaaS products, investors and entrepreneurs are shifting focus back to tech-enabled services. Integrating AI deeply into physical services and workflows is now seen as creating more defensible, lasting value than pure software, reversing a years-long trend.

In 2026, the AI investment narrative will expand from foundational model creators to companies building applications and services. It also includes sectors enabling AI growth, such as energy generation and data centers, offering a wider range of investment opportunities beyond the initial tech giants.

Despite massive investment in chips (NVIDIA) and models (OpenAI), it is not yet clear where long-term value will concentrate. The entire stack is in flux. Models could be commoditized by open source, chips could face historical commoditization cycles, and new AI-native apps could capture the most value. We are only in the early innings of a 30-year shift.

Value in the AI stack will concentrate at the infrastructure layer (e.g., chips) and the horizontal application layer. The "middle layer" of vertical SaaS companies, whose value is primarily encoded business logic, is at risk of being commoditized by powerful, general AI agents.

AI companies are pivoting from simply building more powerful models to creating downstream applications. This shift is driven by the fact that enterprises, despite investing heavily in AI promises, have largely failed to see financial returns. The focus is now on customized, problem-first solutions to deliver tangible value.