History shows the ultimate beneficiaries of technological waves are often not the initial darlings. Facebook and Google became internet giants long after the dot-com bubble. This suggests investors should be wary of paying high valuations for today's hyped AI companies, as the true long-term winners may not even exist yet.

Beyond AI infrastructure, Lone Pine's "Revenge of the Dinosaurs" thesis posits the next wave of value creation will come from large, established companies. These incumbents will adopt AI to slash costs and boost efficiency, leading to significant profit growth and making them the next compelling AI investment theme.

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.

The true financial windfall from AI won't come from hyped, "AI-native" companies like OpenAI. Instead, established giants like Meta and Amazon will generate massive shareholder value by applying AI to optimize their existing, scaled operations in areas like ad targeting, logistics, and robotics.

If AI is truly transformational, its greatest long-term value will accrue to non-tech companies that adopt it to improve productivity. Historical tech cycles show that after an initial boom, the producers of a new technology are eventually outperformed by its adopters across the wider economy.

AI should be viewed not as a new technological wave, but as the final, mature stage of the 60-year computer revolution. This reframes investment strategy away from betting on a new paradigm and towards finding incumbents who can leverage the mature technology, much like containerization capped the mass production era.

As AI commoditizes software, the most defensible businesses are no longer asset-light SaaS models. Instead, companies with physical world operations, regulatory moats, and liability are safer investments. Their operational complexity, once a weakness, now serves as a formidable barrier against pure AI-driven disruption.

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.

Oren Zeev argues against the narrative that AI will kill all incumbents. He believes businesses with operational complexity, deep data moats, and strong distribution are not easily disrupted. These companies are more likely to leverage AI to their advantage, while simpler software companies are at greater risk.