Goldman Sachs Issues Warning: Surging AI Capital Spending Heightens Stock Risks

International investment bank Goldman Sachs has released its latest industry research report, issuing a risk warning to global investors: Global cloud giants, AI technology enterprises, computing infrastructure, and capital expenditures for chip purchases have continued to increase. The valuation bubble in the AI sector, as well as the risks of lower-than-expected profits, have rapidly accumulated. The volatility of AI stocks has risen, and the risk of sectoral correction has significantly increased. This is to cool down the booming AI investment craze.

According to the report, AI capital spending of leading cloud providers has outpaced industry expectations by a wide margin. Wall Street estimates global AI capital expenditure of cloud firms will hit $920 billion in 2027, while Goldman Sachs deems the estimate overly conservative. Based on expansion plans of four tech giants including Google, Amazon, Meta and Microsoft, the figure could peak at $1.4 trillion in 2027. The four giants’ combined AI capital spending will reach $725 billion in 2026, surging 77% year-on-year, mainly flowing into AI chips and data center construction.

Goldman Sachs pointed out that rising capital spending has triggered three major investment risks. First, squeezed corporate profits. AI infrastructure features long investment cycles and high depreciation costs. Concentrated depreciation provisions in the next two to three years will erode corporate net profits continuously, and it is much harder for current AI investment to generate reasonable returns than early Internet investment.

Second, inflated sector valuations. AI concept stocks have seen rocketing valuations since the launch of ChatGPT, with stock prices tied to computing orders rather than actual operating revenue. AI commercialization advances slowly at present, and most mid-and-small-sized AI enterprises register revenue growth without profit growth. Their high valuations lack solid earnings support, and slowing capital spending will trigger valuation slumps directly.

Third, supply-demand imbalance. Massive computing infrastructure expansion will lead to oversupply of AI computing capacity. Meanwhile, tightened corporate digital transformation budgets and sluggish AI purchasing demand will lower computing utilization rates, drag down return on investment and weigh on AI stock performance.

Leading US AI stocks have led market gains with extreme institutional capital clustering. As of mid-June, the Nasdaq AI Index has climbed over 32% year-to-date, with bellwethers like Nvidia and Microsoft hitting record-high market values. Passive index funds and hedge funds hold AI sector positions at a five-year high. Goldman Sachs stated the AI market has entered a return-verification stage, with Q2 tech earnings reports acting as a critical watershed. Disappointing AI revenue and gross margin data will trigger a sector-wide valuation correction, and homogenous trading will worsen panic sell-offs once negative news emerges.

On investment strategies, Goldman Sachs advised investors to abandon blanket bullish bets on AI. Investors should steer clear of concept stocks with high capital consumption and no real revenue, and prioritize cash-rich leading firms with mature AI monetization capabilities. It also recommended cutting AI exposure and allocating defensive sectors such as consumer staples and utilities to hedge risks. Retail investors are warned against chasing high-flying upstream computing stocks, whose performance hinges heavily on procurement orders from tech giants and faces drastic price swings.

Industry analysts noted the current AI rally is driven by supply-side capital outlays instead of end-user consumption demand. Small and medium-sized enterprises remain reluctant to adopt AI tools, and low B-end monetization efficiency can hardly digest soaring new computing capacity. Some institutional investors have started trimming positions on overvalued AI stocks, with safe-haven capital rotating to other assets. Goldman Sachs’ warning marks a strategic shift of AI investment logic from scale expansion to profit realization. The industry has entered a reshuffling phase, ending the broad-based AI rally. Market divergence will intensify, leaving more structural opportunities than holistic upside in the sector