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Bernstein analyst Daniel Zhu said that although previous optimistic judgments about the short-term trend of AI-related stocks were proven wrong, the current reasons for being bearish on AI are still not persuasive enough. The stock prices of the network equipment and optical communication companies covered by the bank have fallen by 12% to 42%, but the five companies that have announced results have all given performance guidelines that are higher than market expectations, indicating that the decline in stock prices is mainly due to shrinking valuations rather than worsening profit expectations. Bernstein pointed out that the market is mainly concerned about whether commercial returns from AI companies can support huge infrastructure investments, and whether land and power restrictions will slow down data center construction. Regarding the former, the bank believes that the slowdown in AI companies' revenue growth in September may only be a temporary pricing fluctuation. Revenue performance has improved in October, and AI usage is still growing strongly. It is estimated that by 2027, the scale of AI infrastructure put into operation by large cloud service providers will reach about 1.2 trillion US dollars. According to the 15% return on investment requirement and 24% net profit margin, it will require about 729 billion US dollars in terminal AI expenses. Although this scale is not inevitable, it is still feasible. Regarding the latter, Bernstein believes that land and power restrictions will have a limited impact on the 2027 project, and the risks are likely to focus more on 2028. Based on the above judgment, Bernstein believes that there is currently no sufficient reason to believe that AI infrastructure investment will substantially slow down, so maintain a long-term optimistic stance. However, the fact that fundamentals have not deteriorated significantly does not mean that stock prices can quickly recover. The bank expects that the AI sector may experience a technical rebound in the short term, but due to the lack of obvious catalytic factors until January next year, it will still take time to fully repair it.
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Bernstein analyst Daniel Zhu said that although previous optimistic judgments about the short-term trend of AI-related stocks were proven wrong, the current reasons for being bearish on AI are still not persuasive enough. The stock prices of the network equipment and optical communication companies covered by the bank have fallen by 12% to 42%, but the five companies that have announced results have all given performance guidelines that are higher than market expectations, indicating that the decline in stock prices is mainly due to shrinking valuations rather than worsening profit expectations. Bernstein pointed out that the market is mainly concerned about whether commercial returns from AI companies can support huge infrastructure investments, and whether land and power restrictions will slow down data center construction. Regarding the former, the bank believes that the slowdown in AI companies' revenue growth in September may only be a temporary pricing fluctuation. Revenue performance has improved in October, and AI usage is still growing strongly. It is estimated that by 2027, the scale of AI infrastructure put into operation by large cloud service providers will reach about 1.2 trillion US dollars. According to the 15% return on investment requirement and 24% net profit margin, it will require about 729 billion US dollars in terminal AI expenses. Although this scale is not inevitable, it is still feasible. Regarding the latter, Bernstein believes that land and power restrictions will have a limited impact on the 2027 project, and the risks are likely to focus more on 2028. Based on this judgment, Bernstein believes that there is currently no sufficient reason to believe that AI infrastructure investment will substantially slow down, so maintain a long-term optimistic stance. However, the fact that fundamentals have not deteriorated significantly does not mean that stock prices can quickly recover. The bank expects that the AI sector may experience a technical rebound in the short term, but due to the lack of obvious catalytic factors until January next year, it will still take time to fully repair it.
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