Is AI Trading Shifting from Chips to Cloud Giants?
TL;DR · Morgan Stanley strategist Michael Wilson believes that AI investments could shift from semiconductors to cloud infrastructure giants like Microsoft, Amazon, and Meta. · The market is divided on whether this rotation is a sign of AI trends spreading or if investors are starting to question the returns on massive AI investments. · Related stocks: MSFT, AMZN, META, NVDA, AMD, SOXX, SMH
Morgan Stanley's U.S. equity strategist Michael Wilson recently suggested in his strategy outlook that the momentum in semiconductor stocks is waning, and investors should focus more on AI cloud giants like Microsoft, Amazon, and Meta. According to Invezz on July 6, Wilson's team believes that some previously underperforming cloud infrastructure giants are becoming more attractive after fluctuations in chip stocks.
This statement has been amplified in the market because it reframes the question of AI trading. For the past two years, capital has primarily focused on “who supplies AI.” Now, the market is beginning to ask, “who can turn AI infrastructure into revenue and profit?”
Companies like Nvidia and AMD are upstream suppliers in the AI construction cycle. Microsoft, Amazon, and Meta, on the other hand, purchase chips, build data centers, and monetize through cloud services, advertising, and AI products.
If chip price increases are solely driven by orders, then it would be sufficient for capital to continue betting on upstream. However, after a significant rise in semiconductor stocks in the first half of the year, there has been considerable volatility recently, leading to a different question: Is the AI theme cooling down, or is capital merely rotating within AI?
Chip Volatility Lowers the Odds of Chasing Highs
Wilson's judgment is based on a straightforward observation: semiconductor trading has become very crowded. The Philadelphia Semiconductor Index previously rose due to AI demand but experienced a notable pullback in early July, followed by a rebound in chip stocks.
A more reasonable explanation is that semiconductor stocks have already priced in many optimistic expectations. As long as valuations and price increases are sufficiently high, even if the fundamentals do not deteriorate, capital may choose to realize profits.
For investors, the question is no longer “Are chips good?” but rather “Is it still worth chasing chips now, or do other AI assets offer better odds?” When the upstream has already risen, the market will naturally look for previously lagging segments.
In Wilson's framework, this rotation represents a shift within AI trading towards leading assets. The theme has not disappeared, but capital is now demanding new proof. Previously, the focus was on orders and deliveries; now it is on usage, revenue, and profit.
Cloud Giants Are Capturing Monetization Expectations
Cloud giants have become a destination for capital because they hold two identities. On one hand, they are among the largest buyers of AI chips and data centers. On the other hand, they are also the most likely to commercialize these investments.
Microsoft can embed AI into office software and cloud services, Amazon has a massive cloud business, and Meta can use AI for ad recommendations, content generation, and foundational models. Compared to pure upstream companies, they also have their existing core businesses providing cash flow buffers.
This is precisely where the market is re-pricing. In the past, investors were willing to pay for “the intensity of AI construction,” with the most direct beneficiaries being the chip and equipment chains. Now, capital is beginning to pay for “the potential for AI monetization,” and the valuation logic of cloud giants will be re-discussed.
However, this has not yet been validated. If Microsoft, Amazon, and Meta are to take the baton, they cannot rely solely on the fact that they have “purchased a lot of chips”; they must also demonstrate that capital expenditures can translate into higher cloud revenues, stronger advertising efficiency, or more stable profit margins.
Capital Expenditure Discipline Changes Pricing
The pace of capital expenditures by cloud giants is also an important variable. In simpler terms, companies are no longer just competing on who builds more data centers, but are starting to evaluate whether every dollar invested in AI can yield returns.
In the short term, this could be positive for cloud giants' stock prices. Previously, the market was concerned that they would continue to burn cash for the AI race, dragging down free cash flow and profit margins. If management signals more restrained spending, investors will be more likely to accept the narrative that “AI investments are entering a rational phase.”
The same situation may not be friendly for upstream. Chip companies need customers to continue placing orders. If cloud giants' capital expenditures merely shift from rapid growth to selective growth, the impact may be limited. However, if spending slows more than expected, semiconductor orders and valuations could continue to be under pressure.
Thus, the transition to cloud giants does not mean the logic of chips is invalid. Both remain on the same AI industry chain. The change is that the market is no longer rewarding just the scale of investment but is also beginning to reward investment efficiency.
S&P 8000 Points Requires Market Expansion
Morgan Stanley has raised its year-end target for the S&P 500 from 7800 to 8000 points in its mid-term outlook. This target provides a larger context for the rotation: if the index is to rise further, it cannot rely solely on a few semiconductor stocks repeatedly lifting it; more heavyweight stocks must embrace the AI narrative.
From an index perspective, the weight and profit stability of Microsoft, Amazon, and Meta are sufficiently important. If they become the new leading forces, the AI trend will expand from a single upstream trade to a broader re-evaluation of tech stock profits.
The risk is that price performance can sometimes obscure the nature of capital. If capital is merely withdrawing from chips to seek refuge in cloud giants, and if cloud giants do not form sustained buying pressure, this is not healthy expansion but merely a defensive migration after a crowded trade loosens.
The two scenarios may appear similar in short-term trends but have different implications for the index. The former corresponds to the AI bull market entering the monetization phase, while the latter corresponds to investors beginning to doubt the returns on AI investments, merely seeking relatively safe docking points within tech stocks.
Earnings Data Determines Rotation Space
This rotation will ultimately hinge on a few sets of hard data. The next round of earnings reports from Microsoft, Amazon, and Meta will need to provide clearer clues about AI revenue. Whether capital expenditure guidance shows a mild slowdown or a significant contraction, and whether profit margins can prove that AI investments have not eroded the quality of existing businesses.
For chip stocks, Nvidia and AMD's orders, guidance, and customer demand are equally critical. If upstream guidance remains strong, the semiconductor pullback may merely be a valuation digestion, and capital could still return to the chip chain. If guidance weakens, the rotation framework will be more readily accepted by the market.
The more appropriate judgment now is not that the chip era is over, nor that cloud giants will inevitably take over. AI trading is transitioning from supply-side enthusiasm to monetization-side verification. In the next round of earnings reports, whether capital expenditures, cloud revenues, and profit margins can all hold steady will determine whether this rotation is a short-term hedge or whether the AI mainline is entering the next phase.
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