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.

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While AI's market performance has been concentrated in the tech sector, its greatest future value will be unlocked as it transforms other industries like healthcare, logistics, and consumer goods. Buchwald believes investors are underestimating this broadening impact, which will create new winners and losers across the entire economy.

The most significant societal and economic impact of AI won't be from chatbots. Instead, it will emerge from the integration of AI with physical robotics in sectors like manufacturing, logistics (Amazon), and autonomous vehicles (Waymo), which are currently under-hyped.

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.

While the market seeks revenue from novel AI products, the first significant financial impact has come from using AI to enhance existing digital advertising engines. This has driven unexpected growth for companies like Meta and Google, proving AI's immediate value beyond generative applications.

The true economic revolution from AI won't come from legacy companies using it as an "add-on." Instead, it will emerge over the next 20 years from new startups whose entire organizational structure and business model are built from the ground up around AI.

AI favors incumbents more than startups. While everyone builds on similar models, true network effects come from proprietary data and consumer distribution, both of which incumbents own. Startups are left with narrow problems, but high-quality incumbents are moving fast enough to capture these opportunities.

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.

Unlike previous tech waves, AI's core requirements—massive datasets, capital for compute, and vast distribution—are already controlled by today's largest tech companies. This gives incumbents a powerful advantage, making AI a technology that could sustain their dominance rather than disrupt them.

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.