Toilet maker Toto saw its stock soar because its expertise in porcelain was repurposed to make a critical component for AI chip manufacturing. This shows how legacy companies can unlock significant value by identifying and scaling niche capabilities for high-growth tech industries.
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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.
Instead of focusing only on new technology, it's crucial to see how old technologies disrupt industries in new ways. Mala Gaonkar cites lithium-ion batteries, invented in 1976, revolutionizing the modern auto industry, and gaming GPUs from the past now powering the AI boom.
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 most transformative opportunities for founders lie not in crowded SaaS markets but in applying an advanced technology mindset to legacy industries. Sectors like lumber milling, mining, and metalwork are ripe for disruption through automation and robotics, creating massive, untapped value.
Significant disruption often comes from applying mature technologies in novel contexts, not just from new inventions. Gaonkar points to 1970s lithium-ion batteries revolutionizing EVs and old gaming GPUs now powering the AI boom as prime examples of this powerful investment thesis.
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.
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.
Critics question whether deep tech startups are doing "novel science." However, the strategic goal is often not a new discovery, but making a proven but abandoned technology (like nuclear fission) economically viable and scalable again. This demonstrates that for reindustrialization, effective execution on proven tech can be more valuable than chasing purely scientific breakthroughs.
