The “Magnificent 8”—including Alphabet, Amazon, Apple, Meta, Microsoft, Netflix, Nvidia and Tesla—built their leadership through dominance in their respective sectors (retail, automotive, software, consumer products, etc). If you were buying this group of companies 10 years ago, you would have had a pretty diverse basket of different industries.
Over time, their near monopolies were a primary driver of exceptional growth, heavily influencing the S&P 500 and increasing concentration risk for passive investors.
Now, all eight companies are investing aggressively in AI, entering a shared arena for the first time. They might have slightly different twists on how they’re applying AI but they’re all really competing in the same vertical. This is a departure from what we’ve seen in the past.
Economics 101 dictates this convergence in strategy means future growth will not be as easy as it was in the past. Watch this video for more context on what this means for investors:
Key Takeaways:
Increased Risks and Potential Normalization
The companies’ prior economic success stemmed from outsized influence in specific sectors. Now, it appears as though all of these companies are chasing the same opportunities, which we believe could lead to more normalized returns. It is possible these stocks could lead the market down during the next pullback or if we enter a longer economic cycle other previously overlooked businesses might “catch-up”.
Historically, major trends have reverted over time. And we believe that will happen here too.
What This Means for Investors
Diversifying strategies can be crucial to managing the risks of concentrated exposure.
The Magnificent 8’s transition from industry giants to direct competitors in AI marks a pivotal shift that we believe could lead to elevated risks for concentrated passive portfolios. Staying informed and agile will be essential for navigating this changing market reality.
Click here to learn how we can help navigate this shift.
Full Transcript of the video:
Measure for Algorithmic Investment Models. Going to talk to you today about a pretty popular topic, but hopefully share some unique insights. That’s the Mag 8, or the eight largest companies in the S&P 500.
Historically, we’ve talked about these companies mostly in a portfolio context—the idea that the S&P 500 is historically extremely concentrated because of the success of these businesses. That presents unique risks for investors.
Today, we’ll focus a little bit about maybe what the future of these companies might look like, and how the past isn’t a perfect predictor of that—as it rarely is.
Each of these companies has really come to dominate their own unique niche. If you were buying this group of companies 10 years ago, you would have had a pretty diverse basket of different industries. You would have had an automaker in Tesla, a consumer products maker in Apple, a retailer, social media in Meta and Google.
But now, you’ve seen them all competing under a singular vector, and that’s AI. So every one of these businesses is spending on chips, they’re trying to build AI models. Maybe they have slightly different twists on how they’re going to apply that, but they all really are competing in the same vector. That is a lot different than what the past has looked like.
The amazing economics you saw in most of these businesses were a result of them being near monopolies. In fact, most investors would have predicted that the bear case for these stocks was antitrust—that the government would see them as too large and too powerful and seek to break them up. That hasn’t really occurred so far.
But now, perhaps market forces will actually bring in the economics of these businesses. AI is really just the current iteration of that. I think because these companies have become so big and they’re so ambitious, they’re really going to throw money at every new big idea in the future—and that has implications for the economics.
This is just, like I said, the beautiful performance you’ve gotten—the results in these businesses thus far have been as a result of dominating a subset of the market. Now, if they’re all chasing kind of these big opportunities, returns should be lower than they have been.
So the implication for investors is that this top-heaviness will play out negatively versus a more balanced portfolio. These stocks could lead the market down in the next downturn if, say, AI capital spending declines and that’s what leads the next downturn. Or perhaps we have a longer economic cycle and overlooked, more suitable businesses catch up and correct for the concentration that way.
It’s rarely clear—without the benefit of hindsight—what is going to catalyze a major trend. But historically, major trends have reverted over time. We think that will happen here.
Just this idea of competition is kind of one we’re throwing out there for how these companies may become more normal in the future, whereas they’ve obviously been extremely abnormal in the past.
If you’d like to talk with us directly about this or any other topic, please feel free to reach out. We’d be happy to continue the discussion, and thank you.
Disclosures:
Copyright © 2025 Algorithmic Investment Models LLC (AIM). All rights reserved. All materials appearing in this presentation are protected by copyright as a collective work or compilation under U.S. copyright laws and are the property of Algorithmic Investment Models. You may not copy, reproduce, publish, use, create derivative works, transmit, sell or in any way exploit any content, in whole or in part, in this presentation without express permission from Algorithmic Investment Models.
Investors should recognize the limitations of AI, seek professional advice, and carefully assess their risk tolerance and financial situation before making investment decisions. There are risks when using AI including but not limited to, lack of predictability, reliance on historical data, and sensitivity to market volatility may impact investment outcomes. Technology-related risks and the dynamic nature of market conditions further contribute to potential uncertainties.
Performance data referenced are for market indexes only, for the time period stated and are gross of fees. One cannot invest directly in an index.
“Mag 7” referenced in this video are a group of the 7 largest companies by market capitalization which includes: Alphabet, Amazon, Apple, Meta Platforms, Microsoft, Nvidia, and Tesla. “Mag 8” is the Mag 7 plus Netflix.
Diversification does not ensure a profit or guarantee against a loss. As with all investments, there are associated inherent risks including loss of principal. Stock markets, especially foreign markets, are volatile and can decline significantly in response to adverse issuer, political, regulatory, market, or economic developments. Sector investments concentrate in a particular industry and the investments’ performance could depend heavily on the performance of that industry and be more volatile than the performance of less concentrated investment options. Foreign securities are subject to interest rate, currency exchange rate, economic, and political risks, all of which are magnified in emerging markets. The risks are particularly significant for ETFs that focus on a single country or region. The ETF may have additional volatility because it may be comprised significantly of assets in securities of a small number of individual issuers. Fixed Income investments are subject to inflationary, credit, market and interest rate risks.
ETFs trade like stocks and are subject to investment volatility and the potential for loss. The principal amounts invested in ETFs are not protected, guaranteed or insured. The AIM investment strategies may not be appropriate for everyone. Due to the periodic rebalancing nature of our strategies, they may not be appropriate for those investors who desire regular withdrawal or frequent deposits.
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