Making sense of AI, equity valuations, and how to avoid a bubble
BY FERNANDO DE FRUTOS, CFA, PhD | OCTOBER 2025
CIO of Boreal Capital Management AG
- AI and Market Psychology: The surge in AI-driven investment is reshaping expectations across markets, yet valuations outside the hyperscalers remain surprisingly anchored. Investors may still be underpricing the magnitude—and breadth—of the coming transformation.
- Optionality vs. Hype: Technological change expands uncertainty, but it also raises the value of “real options”. The task for investors is not to predict the future, but to position for asymmetry—capturing AI’s upside without succumbing to speculative excess.
- Portfolio Positioning: In an era of exponential innovation, conventional diversification may fall short. A pragmatic barbell strategy—combining exposure to AI leaders with the underappreciated optionality in the broader market—offers the most balanced way to participate in progress.
There is a charged tension in the markets — the sense of energy accumulating before a storm. The surge of AI breakthroughs and the frenzy of capital pouring into computing power have no precedent. The question for investors is not whether that superficial tension will break, but how: in the form of a bubble that bursts into the air, or a volcanic eruption — a force that disrupts the surface yet expands the landscape beneath.
The Age of Hyperscalers
Large Language Models are moving up the value chain with uncanny speed, following the same path that emerging economies once used to converge with industrialized nations. ChatGPT, Gemini, and their peers now perform at expert levels — writing code, passing professional exams, and increasingly mastering human domains once thought unreachable by machines.
The world’s largest technology companies are racing to build data centers at a pace reminiscent of the 19th-century railroad boom. It is frontier land again—governed by the old mantra, “Build it, and they will come.” Governments have joined the race with wartime intensity. Export controls on advanced microchips now resemble arms embargoes: ASML’s most sophisticated lithography systems shipped to Taiwan include remote-disable features—à la “Mission: Impossible”—to prevent their capture in the event of a Chinese invasion. In the U.S., the government has even taken a strategic stake in Intel—a quasi-nationalization that would have been unthinkable in the pre-AI era.
Corporate maneuvers are equally extraordinary. Cross-shareholdings, strategic alliances, and massive capital outlays have made the sector look increasingly like Japan’s keiretsu conglomerate system before the 1980s bubble. Nvidia invests billions in its own clients, Microsoft bankrolls OpenAI while competing with it, and hyperscalers are at once each other’s customers and suppliers. Such “circularity” amplifies both innovation and fragility.
If AI Stalls
If AI proves slower to commercialize than hoped — if models plateau or energy costs cap scalability — the fallout could be substantial. Hyperscalers would face massive write-downs on projects tied to what is now a $7 trillion global capex wave, shaving points off GDP and investor optimism alike.
The good news is that AI revenues still represent only a small share of median corporate earnings, with most growth concentrated in a handful of hyperscalers. A disappointment would likely trigger a cyclical correction rather than a systemic crisis—a 20–30% drawdown typical of recessions. As in past waves of innovation, setbacks tend to delay, not derail, progress. The dot-com era ended painfully for investors but brilliantly for civilization: the internet kept its promise once valuations collapsed. AI may do the same.
If AI Erupts
The alternative is far more explosive. If AI continues advancing — if it truly augments or even surpasses human intelligence — then we are not just talking about incremental productivity. We are talking about a step change in the very rate of knowledge creation.
Economists typically model technological progress as an exogenous variable, but AI could make it endogenous — technology that improves technology. In that case, the upper bound for earnings growth dissolves, and equity valuation becomes an exercise in philosophical speculation: What multiple do you assign to infinite learning?
The potential implications of reaching the technological singularity—the point at which machine intelligence surpasses human cognitive capacity—are so immense that fears of social disruption are understandable. We will need rules, ethics, and perhaps humility to manage what we are unleashing. Yet even if we are closer to that theoretical inflection point than anyone could have imagined just a few years ago, it remains highly unlikely to occur within the typical five-to-ten-year investment horizon in which portfolios are managed. As John Maynard Keynes famously remarked, “in the long run we are all dead.”
In the meantime, investors should not fear AI as a threat to humanity, but rather embrace it as an insurance policy for it. Until the day machines can vote or hold a bank account, humans remain the parents—guardians and beneficiaries—of a wunderkind whose genius we are only beginning to discover.
Valuations and Optionality
So how should investors approach valuations under this dual regime of fear and wonder? First, recognize the asymmetry. Unlike the dot-com boom, AI exuberance is concentrated, not generalized. The optionality of artificial intelligence is priced into microchip producers and hyperscalers, but barely reflected in the rest of the market. The S&P 500 Equal-Weighted Index — a better proxy for the average stock — trades today at a price-to-earnings ratio of around 20×, almost identical to its long-term average. In other words, there is no generalized bubble — only pockets of it.
Second, understand the nature of that optionality. Every stock can be thought of as the sum of two components: the going concern (the cash flows we can forecast) and the option on the unknown. Technological revolutions expand the latter. Companies like Tesla, or Nvidia itself, trade at valuations that embed this optional value — the right, not the obligation, to change the world again.
Conclusion: Forget Diversification (for Now?)
Technological breakthroughs always bring more uncertainty. And uncertainty, paradoxically, increases the value of “real options” while eroding the precision of traditional valuation metrics. That is not a flaw—it is the price of progress.
The challenge for investors is to capture the optionality without overpaying for the hype. The S&P 500 Equal-Weighted Index serves as a good thermometer of how much exuberance is priced into equities — and today, it shows surprisingly little, perhaps a lingering trauma from the dot-com bubble. That caution now looks excessive. Even with today’s level of technology, it is hard to imagine that AI will not lift all boats, improving corporations’ cost structures and revenue bases in the years ahead — and far more so if the technology keeps surprising us.
With the Fed shifting toward rate cuts, fiscal policy remaining expansionary, and earnings still growing even without an AI tailwind, the macro backdrop looks increasingly constructive. Combine that with the sheer magnitude of the technological opportunity, and the result is a risk-return profile skewed in favor of equities.
Of course, the old market adage still applies: “It’s never a good time to buy equities.” The price of this positive asymmetry is abandoning the comfort of investors’ rulebooks. One of their maxims—“never put all your eggs in one basket”—sits uneasily with the exceptional nature of the moment.
The pragmatic approach may be a barbell strategy: on one side, the cheap optionality embedded in non-tech stocks; on the other, the insurance value of being exposed to the companies leading the AI rollout. We are undoubtedly making history from a technological standpoint — but from an investor’s point of view, only time will tell whether “this time is really different.”
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