According to analysis, Christian Mueller-Glissmann, head of asset allocation research at Goldman Sachs Group, has indicated that the wave of artificial intelligence (AI)-fueled earnings surprises that propelled US stocks significantly higher last earnings season is unlikely to be repeated this quarter. Relying solely on corporate results may no longer be sufficient to trigger a new, substantial market rally. While companies are still likely to exceed expectations, "the benchmark for this earnings season has been notably raised."

Mueller-Glissmann points out that investors will shift greater attention to corporate forward guidance and management commentary, seeking signals on whether stock indices can continue their gradual ascent from current levels. Goldman Sachs forecasts that second-quarter earnings growth for S&P 500 index constituent companies will reach 22%, a figure largely in line with the compiled market consensus.

The issue, however, is not whether companies will beat expectations, but rather by "how much" they will exceed them and whether the market will "reward" such outperformance. Last quarter's surprises stemmed primarily from the "non-linear surge" in the AI-related supply chain, particularly explosive demand for chips, servers, and cloud infrastructure.

Current sell-side expectations have already largely priced in these positive factors, with valuations for some leading stocks embedding high growth assumptions. Consequently, even if this quarter delivers beats, the marginal impact will likely be significantly weaker, and the market's reaction to "better-than-expected" results may become more subdued.

Mueller-Glissmann elaborated further, explaining that while upward earnings revisions typically persist for an extended period late in a cycle, "this large wave of earnings surprises linked to AI capital expenditure is most likely nearing its end." Leading US technology companies have planned capital expenditures totaling a massive $725 billion this year for data centers, specialized chips, and networking equipment.

Mueller-Glissmann believes that hyperscale cloud service providers remain in a favorable competitive position due to their substantial holdings of AI infrastructure assets. However, the focus should now shift more towards enhancing operational efficiency and accelerating the commercialization and monetization of AI.

The priorities for the second half of the year should pivot to: improving asset utilization—avoiding redundant construction and idle computing power; strengthening pricing power—converting computational resources into billable cloud service revenue; and optimizing capital allocation—striking a balance between investment and shareholder returns.

"The overarching structural trend of AI remains intact," Mueller-Glissmann emphasized, "but the market will no longer generously reward any story merely associated with AI. Instead, it will become more discerning in evaluating the return on investment for each specific business."