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If you watched the Super Bowl earlier this year, you didn't just see a football game. You saw where corporate America is placing its bets. Nearly a quarter of all commercials featured promotions about AI in some form. Fifteen out of sixty-six ads. Google, Amazon, OpenAI, Anthropic, Meta. Once every four minutes or so.

If that felt familiar, it should. A few years ago, the same airtime was wall-to-wall cryptocurrency. The ads change. The pattern doesn't.

And if you're within a decade of retirement, you might be asking: Should I be doing something about AI in my portfolio?

Let's think through it together.

First, we need to acknowledge that you can't really avoid AI exposure, even if you wanted to.

The seven largest U.S. companies, often called the "Magnificent 7," are all deeply involved in artificial intelligence and now account for roughly a third of the S&P 500's total value. Some reported over $100 billion in capital expenditures on AI infrastructure alone. Own a broad U.S. stock index fund in your 401(k) or brokerage account? You've got meaningful AI exposure built in.

Rotating into other sectors isn't necessarily a clean escape, either. Financials, energy, healthcare, and industrials: companies across all of these industries are likely to position their businesses around AI. The technology isn't sitting neatly in one corner of the market; you can toggle on or off. It's likely to be woven into the economic fabric of nearly every industry.

We've seen this before. During the dot-com bubble in the late 90's & early 2000s, plenty of investors swore off internet-related companies. But looking back, few innovations have been more consequential than the internet. The companies that survived and adapted, along with entirely new ones that emerged, created enormous value over the following two decades.

AI may follow a similar arc. ChatGPT launched in November 2022. We're roughly three and a half years in, very early innings in the game of technological progress. As humans, we tend to overestimate the short-term impact of transformative technologies while underestimating their long-term impact.

The gap between short-term noise and long-term reality is where it's easy to get tripped up.

Voting machines and weighing machines

There's an old investing concept worth revisiting.

In the short term, markets behave like a voting machine. Sentiment, headlines, and momentum drive prices. Voters are simply buyers and sellers in the market. More buyers (up-votes) than sellers (down-votes) on a particular day? Price goes up. More downvotes than upvotes during the day? Price goes down.

Over the long term, markets behave more like what legendary investor Ben Graham called a weighing machine. What gets weighed is whether AI makes companies more efficient, more profitable, and more valuable to their customers.

Both of these systems are operating right now. Quick selloffs followed by quick rebounds in tech stocks? Classic voting behavior. But the S&P 500's forward price-to-earnings ratio sits at 22.4x — well above the historical average of 15.9x as of February 10, 2026 (Clearnomics, LSEG) — and investors have been rotating into sectors like Consumer Staples, Energy, and Industrials. Markets may be starting to weigh more carefully where the value is being created or where more attractive long-term bets might be found.

You don't need to predict who wins the AI race. You don't need to guess which companies will be the next Amazon and which will flame out. You just need to take a step back and recognize which machine you're reacting to when you feel the urge to make changes.

Building for robustness, not prediction

If the answer isn't "predict the AI winners" or "avoid AI entirely," what is it?

Build a portfolio designed for robustness. One that can perform across different economic environments regardless of how any single factor plays out. Don't ask "which stocks should I own?", ask "how does my portfolio respond across different economic regimes?"

Asset classes respond differently depending on the economic environment.

• Stocks usually perform well during economic expansion but struggle in recessions, where bonds and cash tend to hold up better.
• A strengthening dollar has historically favored U.S. stocks, while a weakening dollar often benefits international holdings.
• Interest rates work their own levers: rising rates generally hurt bond prices but improve money market returns, and falling rates flip that relationship.
• Unexpected inflation spikes can pressure both stocks and bonds, but commodities and gold have historically provided some offset.

The point isn't predicting which of these environments we're heading into. A mix designed to respond across all of them means no single trend, AI included, determines your outcome.

From 2009-2022, we largely experienced economic expansion, a strengthening dollar, and generally declining interest rates. That combination has been a powerful tailwind for U.S. stocks and bonds, which is why many portfolios today are heavily weighted toward exactly those asset classes.

Economic regimes shift, though. Building for robustness means preparing for the range of environments that could come next, not just the one we've been in. Past performance across these environments is not indicative of future results, but understanding how different assets have historically responded helps inform a more thoughtful approach.

These principles work whether you're in a managed portfolio or building your own allocation in a 401(k), where you typically have access to U.S. stocks, international stocks, bonds, and cash at a minimum.

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The bottom line

AI is real, and it's here to stay. The long-term economic impact may prove enormous. But we're still in the early chapters of a story that will unfold over the coming decades.

Markets react to AI headlines in the short term and weigh real profitability in the long term. Your portfolio doesn't need to predict the winners and losers. It just needs to be built for robustness across whatever economic environment unfolds.

One place to start: look at your current allocation and ask whether it's positioned for the environment we've been in, or for the range of environments that could come next.

The real risk isn't missing the AI trade. It's abandoning a sound process because the AI noise got so loud you couldn't hear anything else.

Most portfolios were built for the economic environment of the last fifteen years. The next fifteen may look very different. If you're within a decade of retirement and wondering whether your current allocation reflects that reality, that's a conversation worth having. You can reach me at srose@cgfinancial.com.

Spencer Rose is a fee-only financial planner at Christensen Group Financial, specializing in retirement income planning for pre-retirees.

This commentary is for informational and educational purposes only. It does not constitute investment advice or a recommendation to buy or sell any security or adopt any specific strategy. Investment advisory services are offered through Christensen Group Financial, LLC, an SEC-registered investment adviser and wholly owned subsidiary of Christensen Group Inc. Investing involves risk, including possible loss of principal. Past performance does not guarantee future results. All examples are hypothetical and for illustrative purposes only. Christensen Group Financial does not provide tax or legal advice. Always consult your own tax and legal advisors regarding your unique situation.