Writing about the opportunities, risks and economic implications of artificial intelligence presents a similar challenge. Given the recent volatility in AI stocks and the significance of this transformative technology, though, it’s worthwhile to examine the AI trade again.
During the recent Q3 2026 Investment Commentary webinar, attendees asked whether AI stocks are in a bubble. They further questioned: “Is there too much debt behind the buildout?” and “What does the spending mean for the economy and my portfolio?” These are fair questions since AI investment is now a major force in markets and the economy, and it is natural to wonder whether enthusiasm has outpaced reality.²
While AI capabilities are improving quickly, business adoption is slower. Only about one in four U.S. firms uses AI today, ranging from roughly half of firms in the information sector to one in 10 in restaurants and hotels.³ That gap could represent both opportunity and risk. Broader adoption could extend productivity and earnings gains well beyond the technology sector, while slow adoption could delay returns on today’s spending.
Path of Transformative Technologies
History suggests transformative technologies endure, even if investors sometimes overpay in the early days. Major buildouts have sometimes followed a familiar path: breakthrough, investment rush, excess capacity, correction, and then decades of benefit as the technology spreads. Electricity, fiber-optic cables, and the internet changed the world, but much of their long-term value went to the users, not just the initial investors.
The large hyperscalers and semiconductor companies discussed below differ from many dot-com-era firms because they have earnings to support their growth. Hyperscaler earnings are expected to rise about 58% this year, while their stock prices are up about 7%. Semiconductor earnings are expected to more than double. Over time, stock prices have tended to follow earnings.4 Since the 2000 peak of the tech bubble, S&P 500 earnings per share have grown roughly 6.5 times, compared with about five times for the S&P 500 index, excluding dividends.5 But industries that have AI exposure now represent about half the index, so continued earnings growth matters enormously.
Recent results also show the risk of lofty expectations. Several AI leaders fell sharply after Q3 reports, as results or outlooks missed high bars, or companies announced even larger spending plans. When a stock already prices in high growth expectations, a solid quarter may not be enough. A small miss, softer guidance, or higher expenditures can prompt a repricing.
Strong Earnings Picture Overall
The stumbles are a reminder that expectations themselves create risk. Diversifying across company size, investment style, and profitability can provide a cushion, though a diversified portfolio may lag when a narrow group of mega-cap stocks leads. The good news is that the broader earnings picture remains strong: as of October 30, with 60% of S&P 500 companies reporting, 82% of those reporting had exceeded EPS estimates, and blended Q3 earnings growth was 30.2%.6
Clients also ask how much of their portfolio is exposed to AI. That is difficult to answer because AI is woven into the very fabric of our economy. Investment in AI flows along a long value chain and into businesses that use the technology; some links in that chain, including utilities and industrials, are not usually considered “tech.” AI-related industries make up about 51% of the S&P 500, so broad U.S. market investors already have exposure. The question is not whether to own AI, but how to participate without concentrating risk.
At Modera, we do not try to time the market or call bubbles. Instead, we build portfolios designed to help manage concentration risk and maintain exposure to transformational technologies. This is why we include exposure to value-oriented and defensive sectors, small companies in addition to large, and international equities. Emerging markets have AI exposure through chipmakers in South Korea and Taiwan, while developed international markets provide broader AI exposure to themes like banking, defense, and energy. Diversification matters in fixed income, too, as hyperscalers increasingly turn to bond markets to fund capital spending. Treasury, municipal, agency mortgage-backed, and international bonds can all help balance that exposure.
Again, while diversification cannot shield a portfolio from a broad market correction, it remains the foundation of a sound long-term investment plan. An emphasis on quality and disciplined rebalancing also contributes to a resilient strategy that should allow investors to benefit from exposure to transformational technologies like AI without betting on a handful of companies.
Investor Brief: Why It’s Worth Revisiting AI
Sarah DerGarabedian, CFA
Director of Investment Strategy, Principal
Wall Street Journal columnist Jason Zweig once described his job as writing about the same ideas “between 50 and 100 times a year” without sounding repetitive.¹
Writing about the opportunities, risks and economic implications of artificial intelligence presents a similar challenge. Given the recent volatility in AI stocks and the significance of this transformative technology, though, it’s worthwhile to examine the AI trade again.
During the recent Q3 2026 Investment Commentary webinar, attendees asked whether AI stocks are in a bubble. They further questioned: “Is there too much debt behind the buildout?” and “What does the spending mean for the economy and my portfolio?” These are fair questions since AI investment is now a major force in markets and the economy, and it is natural to wonder whether enthusiasm has outpaced reality.²
While AI capabilities are improving quickly, business adoption is slower. Only about one in four U.S. firms uses AI today, ranging from roughly half of firms in the information sector to one in 10 in restaurants and hotels.³ That gap could represent both opportunity and risk. Broader adoption could extend productivity and earnings gains well beyond the technology sector, while slow adoption could delay returns on today’s spending.
Path of Transformative Technologies
History suggests transformative technologies endure, even if investors sometimes overpay in the early days. Major buildouts have sometimes followed a familiar path: breakthrough, investment rush, excess capacity, correction, and then decades of benefit as the technology spreads. Electricity, fiber-optic cables, and the internet changed the world, but much of their long-term value went to the users, not just the initial investors.
The large hyperscalers and semiconductor companies discussed below differ from many dot-com-era firms because they have earnings to support their growth. Hyperscaler earnings are expected to rise about 58% this year, while their stock prices are up about 7%. Semiconductor earnings are expected to more than double. Over time, stock prices have tended to follow earnings.4 Since the 2000 peak of the tech bubble, S&P 500 earnings per share have grown roughly 6.5 times, compared with about five times for the S&P 500 index, excluding dividends.5 But industries that have AI exposure now represent about half the index, so continued earnings growth matters enormously.
Recent results also show the risk of lofty expectations. Several AI leaders fell sharply after Q3 reports, as results or outlooks missed high bars, or companies announced even larger spending plans. When a stock already prices in high growth expectations, a solid quarter may not be enough. A small miss, softer guidance, or higher expenditures can prompt a repricing.
Strong Earnings Picture Overall
The stumbles are a reminder that expectations themselves create risk. Diversifying across company size, investment style, and profitability can provide a cushion, though a diversified portfolio may lag when a narrow group of mega-cap stocks leads. The good news is that the broader earnings picture remains strong: as of October 30, with 60% of S&P 500 companies reporting, 82% of those reporting had exceeded EPS estimates, and blended Q3 earnings growth was 30.2%.6
Clients also ask how much of their portfolio is exposed to AI. That is difficult to answer because AI is woven into the very fabric of our economy. Investment in AI flows along a long value chain and into businesses that use the technology; some links in that chain, including utilities and industrials, are not usually considered “tech.” AI-related industries make up about 51% of the S&P 500, so broad U.S. market investors already have exposure. The question is not whether to own AI, but how to participate without concentrating risk.
At Modera, we do not try to time the market or call bubbles. Instead, we build portfolios designed to help manage concentration risk and maintain exposure to transformational technologies. This is why we include exposure to value-oriented and defensive sectors, small companies in addition to large, and international equities. Emerging markets have AI exposure through chipmakers in South Korea and Taiwan, while developed international markets provide broader AI exposure to themes like banking, defense, and energy. Diversification matters in fixed income, too, as hyperscalers increasingly turn to bond markets to fund capital spending. Treasury, municipal, agency mortgage-backed, and international bonds can all help balance that exposure.
Again, while diversification cannot shield a portfolio from a broad market correction, it remains the foundation of a sound long-term investment plan. An emphasis on quality and disciplined rebalancing also contributes to a resilient strategy that should allow investors to benefit from exposure to transformational technologies like AI without betting on a handful of companies.
1 https://jasonzweig.com/saving-investors-from-themselves-2/
2 https://am.jpmorgan.com/us/en/asset-management/adv/insights/market-insights/guide-to-the-markets/
3 https://am.jpmorgan.com/us/en/asset-management/adv/insights/market-insights/guide-to-the-markets/
4 https://am.jpmorgan.com/us/en/asset-management/adv/insights/market-insights/guide-to-the-markets/
5 S&P Dow Jones Indices LLC, S&P 500 [SP500], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/SP500, November 4, 2026.
6 https://insight.factset.com/sp-500-earnings-season-update-october-30-2026
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