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.
Instead of selling software to traditional industries, a more defensible approach is to build vertically integrated companies. This involves acquiring or starting a business in a non-sexy industry (e.g., a law firm, hospital) and rebuilding its entire operational stack with AI at its core, something a pure software vendor cannot do.
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.
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.
The AI revolution may favor incumbents, not just startups. Large companies possess vast, proprietary datasets. If they quickly fine-tune custom LLMs with this data, they can build a formidable competitive moat that an AI startup, starting from scratch, cannot easily replicate.
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.
Drawing a parallel to the early internet, where initial market-anointed winners like Ask Jeeves failed, the current AI boom presents a similar risk. A more prudent strategy is to invest in companies across various sectors that are effectively adopting AI to enhance productivity, as this is where widespread, long-term value will be created.
The massive physical infrastructure required for AI data centers, including their own power plants, is creating a windfall for traditional industrial equipment manufacturers. These companies supply essential components like natural gas turbines, which are currently in short supply, making them key beneficiaries of the AI boom.
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.