The Risk of Being Right, But Early

Doug Walters, CFA

Artificial intelligence may reshape the economy, but that does not mean investors can predict when enthusiasm will fade. Looking back at the dot-com era, this week’s Insight explores why recognizing risk and successfully timing markets are two very different things.

Line-art illustration of a bridge extending into light fog, with the far end gradually disappearing from view.

Contributed by Doug Walters, David Lemire, Max Berkovich, Matthew Johnson

In December 1996, Federal Reserve Chairman Alan Greenspan questioned whether “irrational exuberance” had unduly elevated asset values. Today, the phrase is usually remembered as a prescient warning about the internet bubble. What is remembered less often is what happened next.

The Nasdaq continued rising for more than three years before reaching its peak in March 2000. In other words, Greenspan may have recognized the risk, but anyone who treated his warning as a signal to abandon technology stocks would have missed an extraordinary advance.

That history feels particularly relevant today.

We have been raising concerns about the amount of money flowing into artificial intelligence. AI infrastructure requires enormous investments in data centers, semiconductors, energy, and supporting technology. While the innovation may be real and economically important, the profitability of this buildout remains uncertain.

Those two ideas may feel contradictory, but powerful technologies often attract too much capital precisely because their promise is so compelling. Enthusiasm attracts investment. Investment produces growth. Growth reinforces enthusiasm. For a time, the cycle can feed on itself.

But how long is “for a time?” That’s the trillion-dollar question.

Markets do not operate on a schedule. Valuations can remain elevated, capital spending can continue, and share prices can rise even as longer-term risks accumulate. Recognizing those risks does not tell us when investor expectations will change and it certainly does not give us a reliable date on which to sell. In 1996, few were better placed to be as well-informed as Alan Greenspan. Yet even he had no idea when the exuberance cycle would end.

Relying on market timing is not a durable investment process.

Investors do not need to decide that AI enthusiasm will end tomorrow. Nor do they need to assume that every dollar being invested will earn an attractive return. Our responsibility is to manage the consequences if expectations prove too optimistic, while retaining exposure if the market continues to advance.

That means watching concentrations, trimming exposures when they become disproportionately influential, and reallocating capital thoughtfully. It means remaining diversified across companies, sectors, asset classes, and investment factors. For tax-sensitive investors, it also means weighing the immediate cost of realizing gains against the less visible risk of allowing a successful position to dominate future results.

These actions are not predictions that a decline is imminent. They are an acknowledgment that we cannot know when enthusiasm will peak. That day could be months or years. Enthusiasm could grow exponentially from here and pop, or it could simply slowly fizzle.

The internet bubble ultimately demonstrated that transformative technology, excessive investment, and extraordinary market gains can coexist for years. The lesson is not to ignore warning signs. It is to respect their limits.

Investors do not need to call the top to act responsibly. They need a process that allows them to participate without becoming dependent on enthusiasm continuing forever. We can be concerned about AI overinvestment and still recognize that markets may continue to rally. In fact, holding both ideas at once may be precisely what disciplined investing requires.

How do we know when irrational exuberance has unduly escalated asset values?
Alan Greenspan, December 5, 1996

One thing to watch

As we await the Fed rate decision next week, we’ll keep an eye on AI spend through earnings reports. Meta is the biggest name reporting this week, but Lam Research and Texas Instruments may provide additional context into how much capital is still flowing into the AI ecosystem. Investors have shown a willingness to reward growth and investment, but over time the focus will likely shift toward whether that spending ultimately generates attractive returns.

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