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.

Like containerization, AI is a transformative technology where value may accrue to customers and users, not the creators of the core infrastructure. The biggest fortunes from containerization were made by companies like Nike and Apple that leveraged global supply chains, not by investors in the container companies themselves.

A safer way to play the AI boom is to invest in companies selling the underlying compute infrastructure rather than the hyperscalers buying it. This strategy captures the upside of the secular trend while avoiding direct exposure to how the massive capital expenditure is funded, which may involve risky credit.

In the AI gold rush, don't bet on the "miners" like Google and Meta, who are spending billions on a new, high-risk game. Instead, invest in the "pickaxe makers"—the essential toll bridges like TSMC and ASML that every AI company must pass through, ensuring your investment has a higher probability of success.

The center of the tech landscape has shifted from data to the underlying infrastructure powering AI. Companies providing core components, like NVIDIA or Cerebras, are akin to those who sold tools during the gold rush, profiting regardless of who found gold.

For a value investor, the AI trade isn't about picking speculative winners. The smarter approach is defensive: avoid companies AI will disrupt ('AI losers') and identify ancillary beneficiaries, like data centers, that can be bought at a discount. This strategy gains exposure to the trend without paying the high premium for direct AI hype.

The AI investment case might be inverted. While tech firms spend trillions on infrastructure with uncertain returns, traditional sector companies (industrials, healthcare) can leverage powerful AI services for a fraction of the cost. They capture a massive 'value gap,' gaining productivity without the huge capital outlay.

Using the invention of the car as an analogy for AI, the most significant returns often come from second-order effects (e.g., LA real estate, gas stations), not just the core technology (cars/LLMs). Investors should look for these ripple-effect opportunities.

The best historical parallel for AI isn't the dot-com boom but containerization. Its greatest beneficiaries were not new shipping companies, but incumbents like IKEA and Walmart that leveraged the efficiency for massive scale. AI's true winners will likely be existing businesses that successfully integrate the technology.