BlockBeats News, August 18th. In a recent report, Ben Snider, Chief US Equity Strategist at Goldman Sachs, pointed out that the S&P 500's second-quarter earnings per share growth rate, excluding some private investment income and other revenue, is currently around 31% year-over-year. Among them, stocks related to AI infrastructure contributed to nearly half of the EPS growth, indicating that AI trading, despite experiencing fluctuations, is still providing substantial support for the market on the profit side.

This assessment aligns well with recent market trends. While the S&P 500 continues to hover near record highs, there is a clear internal divergence among tech stocks: on one side, funds continue to chase NVIDIA, Micron, SanDisk, data centers, power, and optoelectronics in the AI infrastructure chain, while on the other side, they are also waiting to see if AI applications can truly translate into productivity and profit. Goldman Sachs believes that second-quarter earnings reports have already shown that the clearest AI profits currently lie in the infrastructure layer, and the productivity dividend brought by AI adoption has not yet been broadly reflected in the financial statements.

The report mentioned that currently, only about 11% of S&P 500 companies have clearly quantified the productivity improvements brought by AI in coding, customer service, and other processes, and only about 2% of companies directly link AI to profit enhancement. This means that the market is still primarily pricing in the "chip diggers," including chips, memory, servers, cloud capital spending, and power equipment, rather than giving a widespread revaluation to AI-using companies.

However, Goldman Sachs does not believe that the absence of AI applications will weaken the long-term logic. The bank points out that while AI-related spending is still less than 0.5% of S&P 500 revenue, the growth rate is accelerating. Currently, companies mainly support AI investment by cutting or shifting budgets for software, labor, and other areas. If productivity improvements begin to be disclosed by more companies in the future, market focus may shift from AI infrastructure to stocks benefiting from AI adoption.