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Panmure Liberum analysts Joachim Klement and Francisca Reis say an AI-sector downturn could pull the S&P 500 down to 5,000 by the end of 2027. That is a conditional forecast, not a prediction that the decline is certain or already under way. In a report published October 5, 2026, MarketWatch framed the coming earnings and guidance cycle as a test of whether hyperscalers’ AI spending can meet investors’ expectations.
Why AI spending could put pressure on the S&P 500
Klement’s concern is a capex dilemma: either side of the spending debate could unsettle markets. If hyperscalers keep increasing capital expenditure, investors may question the effect on the earnings and valuations of companies that carry large weights in the index. But if spending comes in substantially below elevated expectations, chipmakers and data-center equipment suppliers could face a hit to sentiment.
MarketWatch reported Goldman Sachs’s forecast of $1.2 trillion in hyperscaler capital expenditure in 2027. That figure is a secondhand report in the MarketWatch article; the underlying Goldman Sachs publication was not independently verified. The article does not establish that AI spending has reversed or provide a detailed valuation model for the S&P 500 target.
Klement told MarketWatch, “I think the entire bubble will pop either in 2027 or 2028.” He also said stocks had been resilient: “Stock markets have been remarkably resilient despite more and more obstacles put in their way.” Both statements are his views, not evidence that a downturn is inevitable.
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What earnings and guidance will test
Klement pointed to Q3 earnings, followed by full-year results and 2027 guidance expected in January, as a reality check on company performance and AI investment plans. The key issue for investors is not simply whether companies spend more, but whether results and guidance support the high expectations attached to that spending.
As he put it: “But the upcoming Q3 earnings season and then the full-year earnings and guidance for 2027 in January will provide a critical reality check.” The MarketWatch report does not specify individual companies’ expected spending or earnings thresholds, so this is a broad market watchpoint rather than a company-by-company test.
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Which trades Klement says could offer protection
MarketWatch reported Klement’s preference for defensive areas including food producers and sellers, pharmaceuticals and tobacco. These are sector-level ideas, not individualized recommendations or a guarantee of protection in a selloff. They also do not remove exposure to broader market risks.
Utilities, with a distinction about AI-related valuations
Klement also mentioned utilities, but cautioned against those whose valuations have benefited from perceived AI-related power demand. Within that discussion, he pointed to UK and German infrastructure as preferable. The report does not identify specific securities or give implementation details, so the distinction is about the type of exposure, not a named trade.
Bonds as a possible later haven
The article says bonds could attract demand later in 2027 if an equity decline leads investors to seek havens. That is a conditional possibility and a different timing idea from the reported defensive equity positioning; the article does not specify bond types, maturities or entry points.
How large is the forecasted downside?
Klement’s and Reis’s 5,000 target for the S&P 500 by the end of 2027 is associated in the MarketWatch report with a potential decline of about 35% in their AI-bubble scenario. Both figures are attributed forecasts, not observed market outcomes. MarketWatch’s article also includes point-in-time index and Treasury-yield figures that should not be treated as current market data.
For context, the report said more than 400,000 XLU call contracts traded in a recent session, citing SpotGamma, and described it as one of the utility ETF’s largest call-volume sessions in two years. This is a reported options-volume observation, not proof that investors broadly expect utilities to outperform or that the contracts represent a particular directional view.
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The forecast offers a framework for watching two things: whether hyperscaler spending matches expectations and whether companies can translate AI investment into results that support current market enthusiasm. It does not establish that the AI bubble will burst, validate the 5,000 target, or provide enough detail to select individual securities. The reported sector preferences are Klement’s views, and any investment decision depends on an investor’s circumstances and risk tolerance.
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