The biggest keyword of this US earnings season—AI anxiety

This is an earnings season where fundamentals and market sentiment are seriously diverging. Goldman Sachs believes the core contradiction of this earnings season is: There is a significant disconnect between the strength of corporate fundamentals and the market's panic over AI disruption. Earnings are beating expectations, with revenue growing steadily, but the market's pricing logic is already dominated by the AI narrative.

On March 4, according to Windy Trading Desk, Goldman Sachs’ economic research team stated in its latest report that the S&P 500 fourth quarter earnings season is approaching its end. From a pure performance perspective, it's quite a standout quarter—corporate profits grew 13% year-over-year (only 7% was expected at the beginning of the quarter), with actual revenue growth excluding the energy sector at 4.6%, higher than the 3.5% average during expansion periods over the past fifty years. However, all this is overshadowed by one word: AI anxiety (AI-nxiety).

The bank systematically reviewed three core themes of this earnings season—AI productivity implementation, expectations of AI's impact on employment, and the explosive growth of capital expenditures by ultra-large tech companies. Meanwhile, the "K-shaped economy" narrative is heating up again, but actual sales data shows differentiation is not as severe as the market fears.

Goldman Sachs says uncertainty related to AI is reshaping market pricing logic—industries considered highly exposed to AI automation risk (software, financial services, media & entertainment, etc.) have noticeably underperformed since the beginning of the year; expectations for capital expenditure by ultra-large tech companies have been sharply raised, driving overall business investment to become the strongest component of GDP growth in 2026. Investors need to find pricing anchors between "AI disruption panic" and "delayed realization of AI dividends".

Fundamentals Remain Strong, but Fully Suppressed by the AI Narrative

The report says that hard data this earnings season is undoubtedly positive:

S&P 500 overall profit grew 13% year-on-year, far exceeding the 7% expected at the beginning of the quarter;

Median company profit grew 10%, showing broad-based growth;

Analysts’ revisions for 2026 earnings expectations are positive, breaking the historical trend of downgrading next-year expectations in Q4;

Actual revenue excluding the energy sector grew 4.6% year-over-year, keeping pace with the previous few quarters and above the 3.5% average during expansion periods over the past fifty years.

However, Goldman Sachs thinks these solid numbers are almost entirely ignored at the market level. The frequency of AI topics on earnings calls hit a record high, and investors’ attention is dominated by worries about AI possibly disrupting specific industries.

Goldman Sachs’ data shows that industries more exposed to AI automation—those with a higher proportion of labor costs in revenue and labor more easily replaced by AI—have clearly lagged since the beginning of the year. Software & services, financial services, media & entertainment are among these sectors.

AI Productivity: Heated Discussions, Few Quantitative Outcomes

Goldman Sachs says client discussions focus mainly on three macroeconomic contexts. The first core AI topic this earnings season is productivity improvement, but the data reveals a significant "gap between words and actions":

70% of S&P 500 management mentioned AI on earnings calls, an all-time high;

54% mentioned AI in the context of productivity and efficiency;

Only 10% quantified AI’s impact on specific business scenarios;

Only 1% quantified AI’s actual impact on earnings.

AI adoption among small and medium enterprises is even more delayed: among the broader Russell 3000 constituents, only 50% of management discussed AI; U.S. Census Bureau’s "Business Trends and Outlook Survey" shows fewer than 20% of firms currently use AI in any business function.

Although Goldman Sachs has not found a significant correlation between productivity and AI adoption rate at the macroeconomic level, among companies that have quantified AI’s productivity impact, the median productivity gain is about 30%. The most frequently quantified application scenarios are in customer support and software development.

AI and Employment: Early Warning Signals, No Significant Macroeconomic Impact Yet

According to the report, the second AI topic during earnings season is employment and hiring intention, which is one of the most sensitive issues for the market:

In Q4, the proportion of management discussing AI related to layoffs and hiring freezes rose, though the absolute proportion remains limited;

At the macroeconomic level, Goldman Sachs still finds no significant correlation between labor market outcomes and AI exposure or adoption rate;

However, Goldman points out an early signal worth noting: Among companies discussing AI and labor relations on earnings calls, job vacancies dropped 12% in the past year, while the average decline for all companies was 8%—suggesting some companies may have begun to curb hiring intentions in anticipation of productivity gains from AI.

The report notes that from a longer-term perspective, many business surveys show respondents generally expect AI to reduce their workforce needs, and this impact will grow over time. Goldman’s baseline estimate is: In the long run, AI automation will replace 6%–7% of workers (about 11 million jobs).

Capital Expenditure: Ultra-Large Tech Companies Again Beat Expectations, Driving Overall Business Investment

Goldman Sachs notes the most explosive data this earnings season comes from capital expenditure, particularly by ultra-large tech companies (Amazon, Meta, Google, Microsoft, Oracle):

Analysts raised their expectations for 2026 capital expenditure by ultra-large tech companies by 24% from the start of earnings season, up to $667 billion, a 62% year-on-year increase vs. 2025;

Goldman Sachs believes this number reflects analyst expectations and is a proxy for company guidance, implying ultra-large tech companies’ AI infrastructure investment is still accelerating.

According to the report, overall capital expenditure expectations outside ultra-large tech are also strong, partly due to the "One Big Beautiful Bill Act (OBBBA)" which offers more generous corporate tax incentives:

Analysts expect the median S&P 1500 company to increase capital expenditures by 7% in 2026, up from 3% in 2025;

Industries more impacted by OBBBA tax incentives (with greater capital cost reductions) are expected to see faster capex growth.

Goldman Sachs expects business investment will become the strongest component of GDP growth in 2026, with Q4/Q4 growth at 5.2%. AI investment is expected to contribute about 1.5 percentage points to capex growth, but since much of the expenditure will be on imported equipment, its net contribution to GDP growth will be only 0.1–0.2 percentage points.

K-shaped Economy: Narrative Stronger Than Reality, Low-Income Consumers More Resilient Than Expected

Meanwhile, the "K-shaped economy" narrative is once again rising in this earnings season.

"K-shaped economy"—namely widening divergence in consumption between high-income and low-income groups—is another high-frequency term this season, but Goldman’s data analysis shows the degree of narrative differentiation far exceeds that reflected in actual sales data:

For retailers with stores mostly in low-income zip codes, consumer sentiment scores on earnings calls fell to their most pessimistic level since 2020;

However, these retailers’ nominal same-store sales grew 1.4% year-on-year, accelerating significantly from Q3 2025’s 0.2%;

By comparison, retailers mainly serving middle- and high-income consumers saw same-store sales growth of 2.5%;

The sales performance gap narrowed from 2.3 percentage points in Q3 to 1.1 points in Q4.

However, Goldman Sachs believes there is some exaggeration in the K-shaped economy narrative. Looking ahead to 2026, low-end consumption does indeed face more headwinds:

Reduced immigration will further suppress employment and income growth for low-income groups, and the impact from government spending cuts will be more concentrated on them. Middle- and high-income groups will benefit from new personal tax cuts and stock wealth effects.

Goldman Sachs expects overall consumer spending to grow at a solid pace of about 2.2% (Q4/Q4) in 2026.

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The above content is from Windy Trading Desk.

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