Goldman Sachs: AI capital spending is not near an inflection point; market will scrutinize revenue efficiency.

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Goldman Sachs warns in its daily market report that AI capital spending has not yet reached an inflection point, with major U.S. cloud providers requiring $300 billion in annual AI revenue to justify current investments. Analyst Ryan Hammond estimates hyperscale cloud capex could reach $800 billion in 2026 and $1.1 trillion in 2027. The market will closely monitor how spending translates into profitability. Q2 cloud revenue has already added $70 billion annually, with over $1.5 trillion in backlog. Altcoins to watch may respond to shifts in cloud and AI spending trends.
ME AI Despite pressures from high oil prices and elevated yields, U.S. equities have maintained resilience, with AI-themed stocks continuing to support the technology sector. Goldman Sachs’ latest analysis further shifts market focus toward returns: U.S. leading AI cloud providers will need to generate approximately $300 billion in annualized AI revenue over the coming years to offset their current massive investments; to achieve meaningful returns for cloud providers and sustain high profit margins at the application layer, end users must spend close to $1 trillion annually on AI applications. Goldman Sachs analyst Ryan Hammond expects hyperscale cloud providers’ capital expenditures to reach around $800 billion in 2026, with market consensus estimating about $1.1 trillion for 2027. Goldman’s baseline view is that actual spending in 2027 may still exceed consensus, though the growth rate and degree of upside are expected to gradually slow. For trades already reliant on data centers, GPUs, storage, and networking infrastructure to support AI, capital expenditures have not approached a point of sudden contraction; the market will now closely monitor how much cloud revenue and profit each dollar of investment generates. This report also avoids reducing the AI narrative to a pessimistic outlook. Goldman notes that hyperscale cloud revenue in Q2 has already exceeded pre-AI trends by an additional $70 billion annually, with announced backlog exceeding $1.5 trillion. Enterprise AI procurement remains in its early stages, and recent acceleration in corporate spending will make AI’s impact on company profits clearer over the next several quarters. (Source: BlockBeats)
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