This earnings season is marked by a significant divergence between fundamentals and market sentiment. Goldman Sachs believes the core contradiction lies in the stark contrast between robust corporate fundamentals and market panic over AI disruption. While companies are reporting better-than-expected profits and steady revenue growth, market pricing logic is now dominated by the AI narrative.
According to a recent research report from Goldman Sachs's economic research team, as the S&P 500's fourth-quarter earnings season draws to a close, it has been a remarkably strong quarter from a pure performance perspective. Corporate earnings grew 13% year-over-year, far exceeding the initial expectation of 7%. Actual revenue growth, excluding the energy sector, was 4.6% year-over-year, surpassing the 3.5% average seen during economic expansions over the past fifty years. However, all of this is overshadowed by one term: AI Anxiety.
The report systematically outlines three core themes of this earnings season: the implementation of AI for productivity, expectations for AI's impact on employment, and the explosive growth in capital expenditures by hyperscale technology companies. Concurrently, the "K-shaped economy" narrative has regained prominence, although actual sales data suggests the degree of divergence is not as severe as market fears indicate.
Goldman Sachs states that AI-related uncertainty is reshaping market pricing logic. Industries perceived as highly exposed to AI automation risks, such as software, financial services, and media & entertainment, have significantly underperformed year-to-date. Meanwhile, expectations for capital expenditures by hyperscale tech firms have been substantially revised upwards, positioning overall business investment as the strongest contributor to GDP growth in 2026. Investors need to find a pricing anchor between the "panic over AI disruption" and the "lag in realizing AI benefits."
Fundamentals remain strong but are being overshadowed by the AI narrative. The report indicates that the hard data from this earnings season is unequivocally positive. Overall S&P 500 earnings grew 13% year-over-year, far surpassing initial expectations. Median company earnings growth was 10%, indicating broad-based strength. Analyst revisions to 2026 earnings expectations have been positive, breaking the historical pattern of typically downgrading the following year's estimates in the fourth quarter. Actual revenue growth, excluding energy, was 4.6%, consistent with recent quarters and above the long-term average.
However, Goldman Sachs argues that these solid figures are being almost entirely ignored at the market level. Discussion of AI on earnings calls reached a record high, with investor attention dominated by concerns that AI could disrupt specific industries. Data from Goldman Sachs shows that industries with higher exposure to AI automation—those with a higher proportion of labor costs to revenue, where that labor is more easily replaceable by AI—have significantly underperformed in terms of stock price year-to-date.
On AI productivity, client discussions primarily focused on three macro-related contexts. The first core issue was productivity enhancement, but data reveals a notable "say-do gap." While 70% of S&P 500 management teams mentioned AI on their calls—a record high—and 54% discussed it in the context of productivity and efficiency, only 10% quantified its impact on specific business scenarios, and a mere 1% quantified the effect on earnings. AI adoption among small and mid-sized enterprises is even more lagging. Across the broader Russell 3000, only 50% of management teams discussed AI. Surveys indicate less than 20% of businesses currently use AI for any business function. Although no significant economy-wide correlation between productivity and AI adoption rates has been found yet, among firms that have quantified AI's productivity impact, the median improvement is around 30%, most commonly in customer support and software development.
The second major AI topic was employment and hiring intentions, a highly sensitive market issue. The proportion of management discussions linking AI to layoffs or hiring freezes increased in Q4, though from a low base. At the macro level, no significant correlation has yet been found between labor market outcomes and AI exposure or adoption rates. However, an early signal has emerged: companies that discussed AI and labor on their calls saw a 12% decline in job openings over the past year, compared to an 8% average decline across all firms, suggesting some companies may be curbing hiring in anticipation of AI-driven productivity gains. Long-term surveys indicate a widespread expectation that AI will reduce labor needs, with an estimated 6-7% of workers potentially displaced.
The most explosive data point from the earnings season relates to capital expenditure, particularly from hyperscale tech companies. Analysts have significantly raised their 2026 capital expenditure expectations for these firms by 24% since the start of the season, now projecting $667 billion, implying 62% year-over-year growth from 2025. This suggests AI infrastructure investment is still accelerating. Outside of hyperscalers, overall capital expenditure expectations are also robust, partly due to generous tax incentives. Median capital expenditure growth for S&P 1500 companies is expected to be 7% in 2026, up from 3% in 2025. Goldman Sachs forecasts business investment will be the strongest component of 2026 GDP growth. AI investment is expected to contribute about 1.5 percentage points to capital expenditure growth, but due to significant spending on imported equipment, its net contribution to GDP growth is estimated at only 0.1 to 0.2 percentage points.
Meanwhile, the "K-shaped economy" narrative, referring to a widening divergence in spending between high-income and low-income groups, has been prevalent. However, data analysis suggests the narrative is stronger than the reality in sales data. While sentiment among retailers focused on low-income areas is pessimistic, their nominal same-store sales growth accelerated significantly. The gap in sales growth between retailers catering to low-income and higher-income consumers actually narrowed in the fourth quarter. Goldman Sachs believes the K-shaped narrative is somewhat exaggerated. However, looking ahead to 2026, lower-end consumption does face more headwinds, such as reduced immigration impacting low-income employment and income growth, and government spending cuts. Higher-income groups are expected to benefit from new tax breaks and stock market wealth effects. Overall consumer spending is forecast to grow at a solid pace of approximately 2.2% in 2026.
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