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.

AI is a foundational layer, not a niche. Asking if a company is an 'AI startup' will soon be as meaningless as asking if it has a website. The adoption timeline is radically compressed: what took the internet 15 years for ubiquity will take AI only four, with non-adopters facing extinction.

The ultimate fate of AI is to become a background utility, similar to the power grid. Consumers will no more know who provides their AI "tokens" than they know which hydroelectric dam powers their laptop. This implies a future of low, utility-like returns, not high-margin tech profits.

As powerful AI models become cheap and universally accessible, having one is no longer a defensible moat. The real, lasting advantage for a business now comes from assets that a better model can't easily replace: proprietary customer data, deeply integrated user workflows that are difficult to replicate, and long-term client relationships.

Leading AI models are becoming increasingly similar in capability. This rapid convergence suggests the underlying technology is becoming a commodity, and competitive advantage will likely shift to user interface, distribution, and specific applications rather than the core model itself.

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.

Unlike cable or power companies that benefit from regional monopolies, AI intelligence is a globally competitive, frictionless market. This dynamic is 'so much worse' for business because it allows for perfect arbitrage, driving the price of intelligence toward zero and making it incredibly difficult to build a sustainable, high-margin business on the infrastructure layer.