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AI基建还能投多久?高盛:2-3年不是问题,回报窗口才刚开启

Core Viewpoint - The AI investment cycle is transitioning from "investment" to "returns," but this does not imply a slowdown is a peak. Goldman Sachs indicates that despite a deceleration in growth, AI infrastructure investment will remain sustainable over the next 2-3 years, with cost benefits already being realized and stock prices not yet reflecting this structural change [1][2]. Group 1: AI Investment and Returns - Goldman Sachs categorizes AI value creation into three phases: cost reduction through automation (current phase), reinvestment and rebuilding, and revenue generation through incremental income [2][3]. - AI applications in customer service, sales, and IT are already yielding tangible benefits, with 43% of call centers adopting AI tools and achieving an average operational cost reduction of 30% [2][3]. Group 2: Cost Savings and Future Projections - By 2030, AI automation could save Fortune 500 companies approximately $935 billion, representing about 14% of their total costs, with a net present value return of around $780 billion against a cumulative investment of $350 billion [3][4]. - Major cloud service providers are the primary investors in AI infrastructure, focusing on long-term revenue growth opportunities rather than short-term cost savings, complicating ROI calculations [3][4]. Group 3: Infrastructure Spending and Demand - Concerns about whether infrastructure spending has peaked, particularly regarding training chip inventory and demand, are considered overstated by Goldman Sachs [4][5]. - Large tech companies like Microsoft, Amazon, Google, and Meta are expected to maintain their AI infrastructure investments without significantly compressing profit margins over the next 2-3 years [5][6]. Group 4: New Demand Drivers - Demand for "inference" computing from enterprise clients and government (sovereign AI) is emerging as a new spending driver, especially as small and medium enterprises rapidly expand their deployment of customized models or edge AI applications [6][7]. Group 5: Market Valuation and Stock Performance - The market has partially priced in strong demand expectations for Nvidia's next-generation GPUs, but there is still insufficient valuation for its expanding customer base and the potential explosion of AI inference business [8]. - Broadcom's stock price increase is attributed to clear guidance indicating AI revenue growth of 60% in FY25 and FY26, suggesting that the stock price rise reflects a clearer mid-term fundamental improvement path [8].