Goldman Sachs strategists led by Ryan Hammond argue that analysts trim AI spend forecasts too sharply. They project hyperscaler outlays to reach $1.4 trillion by 2027, up from the current consensus of about $920 billion. The lift hinges on robust cash flows and fresh investment‑grade debt to fund next‑gen server farms and accelerate cloud AI services.

The analysts say higher spend will lift earnings for AI‑infrastructure firms, many of which have already rallied. Yet they warn valuation pressure is rising, noting the median multiple now sits at 26x PE—the steepest level since ChatGPT’s launch. Gains are clustered in semiconductor and power companies, not hyperscalers or memory stocks in the near term.

Oracle’s recent capital‑expenditure miss sparked a dip in its shares and a rally in chipmakers, underscoring the link between data‑center spending and AI supply chains. Investors now weigh whether the sector’s inflated valuations can sustain growth amid tightening credit conditions and whether regulatory scrutiny will slow deployment or if new entrants will dilute returns in the tech sector.

Beyond AI, Goldman’s chief U.S. equity strategist Ben Snider dismisses the SpaceX IPO as unlikely to dent the bull market, reaffirming an 8,000‑point target for the S&P 500 by year‑end. The firm sees continued earnings growth as the engine behind the rally, keeping the market on a steady trajectory while investors monitor policy shifts and supply‑chain bottlenecks globally.