NextFin News - Goldman Sachs strategist Christian Mueller-Glissmann is arguing that the AI trade may be shifting toward a less volatile part of the market just as chipmakers remain the most crowded expression of the theme. His point is not that semiconductors have lost their importance. It is that the market may be rewarding the next layer of AI exposure: the large platform companies that can benefit from artificial intelligence without carrying the same degree of single-sector volatility.
The key tension is between leadership and durability. Chipmakers and other AI capital-expenditure beneficiaries have driven much of the recent advance in the AI complex, but those stocks also sit in the most reflexive part of the trade. They are widely owned, heavily traded through funds and derivatives, and often priced on expectations that can change quickly when the market’s appetite for risk shifts. Big tech, by contrast, offers AI exposure through companies that also earn from advertising, cloud, software, operating systems, and consumer ecosystems.
That distinction matters because Goldman’s own research team is still constructive on equities into 2026, but expects a broadening bull market rather than another year of narrow leadership. In that setting, the relative question is not whether AI spending continues. It is which companies can keep monetizing it with the least dependence on a single volatile factor. If the chip trade becomes more unstable, investors often rotate within the same theme rather than abandon it outright.
Mueller-Glissmann’s argument lands at a moment when the AI market is showing signs of exactly that kind of internal rotation. Semiconductors remain central to data-center build-outs and model training, but the more crowded a trade becomes, the more the market tends to punish it for modest disappointments. The result is a familiar pattern: the most direct expression of a theme can become the least attractive on a risk-adjusted basis.
Why Big Tech Can Look Better When Chips Get Choppy
The first reason big tech can regain favor is that it offers a cleaner way to stay exposed to artificial intelligence. The biggest platform companies still spend heavily on AI infrastructure, but they also have revenue streams that are not tied to a single product cycle. That gives them a cushion when the market starts treating semiconductors as the highest-beta trade in the complex.
Semiconductor stocks, by contrast, are often the purest public-market expression of AI infrastructure demand. That purity is valuable when the theme is accelerating. It is also dangerous when positioning becomes crowded. If investors have already expressed their optimism through exchange-traded funds, options, and momentum strategies, the same trade can unwind quickly once volatility rises.
Goldman’s strategist highlighted exactly that risk by pointing to positioning and leverage across vehicles such as ETFs and options. That is an important distinction. It means the issue is not just earnings or guidance. It is also the market structure around the stocks. A sector can keep growing and still become less attractive if the ownership base is too concentrated and the derivatives exposure too large.
“Big tech stocks could turn more attractive in the artificial intelligence trade as chipmakers show continued volatility,” Christian Mueller-Glissmann said.
That judgment fits the way markets usually behave late in a crowded leadership cycle. They do not necessarily abandon the winning theme. They look for a steadier way to express it. In AI, that steadier way may be the hyperscaler or platform company that monetizes demand across search, cloud, software, commerce, and advertising rather than the chipmaker whose stock is tied much more tightly to the next earnings print and the next positioning squeeze.
There is also a valuation and earnings-visibility argument. Big tech often trades on the market’s willingness to pay for durability, while semiconductors trade on the market’s willingness to extrapolate cyclicality. When volatility rises, the premium for durability can widen. Investors begin to care less about which name has the most torque and more about which one can absorb a drawdown without breaking the broader thesis.
That does not make semiconductors unattractive in the long run. It makes them tactically harder to own when the trade gets crowded. The same characteristic that made them the most powerful AI expression can make them the least forgiving if sentiment turns.
What Goldman’s Broader Outlook Adds to the Argument
Goldman’s broader equity stance helps explain why this is a relative rotation call rather than a bearish market call. The firm’s research team remains constructive on equities for 2026, arguing that earnings continue to grow even if index returns are expected to be lower than in 2025 and leadership broadens out.
Goldman Sachs Research said analysts “remain constructive on equities for 2026 as earnings continue to grow, but forecast lower index returns than in 2025, amid a broadening bull market.”
That backdrop is important because broadening bull markets often change the kind of stocks investors prefer. In a narrow rally, the obvious winners can dominate for a long time. Once the move broadens, capital typically rotates toward names that still participate in the cycle but do so with less instability. Big tech fits that description better than the most volatile chip names do.
The strategist’s argument also reflects a market that has already moved through the first phase of the AI boom. The first phase was about proving that the spend was real. The second phase is about determining who captures the economic rent. Semiconductors are indispensable to the build-out, but platform companies may prove more durable if AI spending turns into recurring usage rather than one-time infrastructure excitement.
That shift matters because markets are forward-looking. They do not pay only for growth. They pay for the quality of that growth. If one part of the AI stack becomes too dependent on short-term momentum, while another part converts the same theme into steady cash flow, the second can become the better bet even if the first remains the more obvious one.
This is why the strategist’s comment should be read as a positioning warning, not a sector obituary. The AI trade is still intact. What changes is the preferred way to own it. When the market starts to question how much leverage and ETF exposure is sitting behind a group of stocks, it often migrates toward the more liquid, diversified, and cash-generative names in the same ecosystem.
What Investors Should Watch Next
The next test is whether chip volatility persists faster than earnings expectations improve. If semiconductors keep swinging while the platform companies continue to report solid demand for AI-related services and infrastructure, the relative case for big tech gets stronger. If chip earnings re-accelerate and positioning cools, the leadership can swing back the other way.
Either way, the important point is that the AI trade is no longer a single track. It is a layered market in which the most direct beneficiaries are not always the best risk-adjusted beneficiaries. That creates room for rotation without forcing a wholesale change in the underlying narrative.
For the broader market, that is a healthier setup than a one-note rally. It spreads leadership across more of the index and reduces the risk that one volatile subsector becomes the sole engine of returns. The AI story still has room to run, but the market may increasingly prefer companies that can monetize it with more balance and less drama.
The lesson from Mueller-Glissmann’s view is simple: in a crowded AI trade, the cleanest exposure is not always the safest one. Sometimes the better way to stay invested is to move one level up the stack.
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